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CODEC                                                         C. Hoene
Internet Draft                                  Universitaet Tuebingen
Intended status: Informational                            June 3, 2011
Expires: December 2011

Measuring the Quality of an Internet Interactive Audio Codec
draft-hoene-codec-quality-01.txt

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Abstract

The quality of a codec has to be measured by multiple parameters
such as audio quality, speech quality, algorithmic efficiency,
latency, coding rates and their respective tradeoffs. During
standardization, codecs are tested and evaluated multiple times to
ensure a high quality outcome.

As the upcoming Internet codec is likely to have unique features,
there is a need to develop new quality testing procedures to measure
these features. Thus, this draft reviews existing methods on how to
measure a codec's qualities, proposes a couple of new methods, and
gives suggestions which may be used for testing the Internet
Interactive Audio Codec (IIAC).

This document is work in progress.

Conventions used in this document

In this document, equations are written in Latex syntax. An equation
starts with a dollar sign and ends with a dollar sign. The text in
between is an equation following the notation of Latex Version 2e.
all Latex equations are already rendered.

Conventions used in this document ............................... 2
1. Introduction ................................................. 4
2. Optimization Goal ............................................ 6
3. Measuring Speech and Audio Quality ........................... 7
3.1. Formal Subjective Tests ................................. 7
3.1.1. ITU-R Recommendation BS.1116-1 ..................... 7
3.1.2. ITU-R Recommendation BS.1534-1 (MUSHRA) ............ 8
3.1.3. ITU-T Recommendation P.800 ......................... 8
3.1.4. ITU-T Recommendation P.805 ......................... 8
3.1.5. ITU-T Recommendation P.880 ......................... 9
3.1.6. Formal Methods Used for Codec Testing at the ITU ... 9
3.2. Informal Subjective Tests ............................... 9
3.3. Interview and Survey Tests .............................. 9
3.4. Web-based Testing ...................................... 10
3.5. Call Length and Conversational Quality ................. 10
3.6. Field Studies .......................................... 12
3.7. Objective Tests......................................... 13
3.7.1. ITU-R Recommendation BS.1387-1 .................... 14
3.7.2. ITU-T Recommendation P.862 ........................ 14
3.7.3. ITU-T Draft P.OLQA ................................ 15

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4. Measuring Complexity ........................................ 15
4.1. ITU-T Approaches to Measuring Algorithmic Efficiency ... 15
4.2. Software Profiling ..................................... 17
4.3. Cycle Accurate Simulation .............................. 18
4.4. Typical run time environments .......................... 19
5. Measuring Latency ........................................... 19
5.1. ITU-T Recommendation G.114 ............................. 20
5.2. Discussion ............................................. 20
6. Measuring Bit and Frame Rates ............................... 21
7. Codec Testing Procedures Used by Other SDOs ................. 22
7.1. ITU-T Recommendation P.830 ............................. 22
7.2. Testing procedure for the ITU-T G.719 .................. 24
8. Transmission Channel ........................................ 25
8.1. ITU-T G.1050: Network Model for Evaluating Multimedia
Transmission Performance over IP (11/2007) .................. 26
8.2. Draft G.1050 / TIA-921B ................................ 27
8.3. Delay and Throughput Distributions on the Global Internet27
8.4. Transmission Variability on the Internet ............... 30
8.5. The Effects of Transport Protocols ..................... 30
8.6. The Effect of Jitter Buffers and FEC ................... 33
8.7. Discussion ............................................. 33
9. Usage Scenarios ............................................. 34
9.1. Point-to-point Calls (VoIP) ............................ 34
9.2. High Quality Interactive Audio Transmissions (AoIP) .... 35
9.3. High Quality Teleconferencing .......................... 35
9.4. Interconnecting to Legacy PSTN and VoIP (Convergence) .. 36
9.5. Music streaming......................................... 36
9.6. Ensemble Performances over a Network ................... 36
9.7. Push-to-talk like Services (PTT) ....................... 37
9.8. Discussion ............................................. 38
10. Recommendations for Testing the IIAC ....................... 38
10.1. During Codec Development .............................. 38
10.2. Characterization Phase ................................ 39
10.2.1. Methodology ...................................... 39
10.2.2. Material ......................................... 39
10.2.3. Listening Laboratory ............................. 40
10.3. Application Developers ................................ 41
10.4. Codec Implementers .................................... 42
10.5. End Users ............................................. 42
11. Security Considerations .................................... 42
12. IANA Considerations......................................... 42
13. References ................................................. 43
13.1. Normative References .................................. 43
13.2. Informative References ................................ 43
14. Acknowledgments ............................................ 48

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1. Introduction

The IETF Working Group CODEC is standardizing an Internet
Interactive Audio and Speech Codec (IIAC). If the codec shall be of
high quality it is important to measure the codec's quality
throughout the entire process of development, standardization, and
usage. Thus, this document supports the standardizing process by
providing an overview of quality metrics, quality assessment
procedures, and other quality control issues and gives suggestions
on how to test the IIAC.

Quality must be measured by the following stakeholders and in the
following phases of the codec's development:

o Codec developers must decide on different algorithms or parameter
sets during the development and enhancement of a codec. These
might also include the selection among multiple codec candidates
that implement different algorithms; however the WG Codec base
its work on a common consensus not on a competitive selection of
one of multiple codec contributions. Thus, measuring the quality
of codecs to select one might not be required.
Besides selection, one is obliged to debug the codec software. To
find errors and bugs - and programming mistakes are present in
any complex software - the developer has to test this software by
conducting quality measurements.

o Typically the codec standardization includes a qualification
phase that measures the performance of a codec and verifies
whether it confirms to predefined quality requirements. In the
qualification phase, it becomes obvious whether the codec
development and standardization has been successful. Again, in
the process of rigorous testing during qualification phase,
algorithmic weaknesses and bugs in the implementation may be
found. Still, in complex software such as the IIAC, correctness
cannot be proved or guaranteed.

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o Users of the codec need to know how well the codec is performing
while manufactures need to decide whether to include the IIAC in
their products. Quality measures play an important role in this
decision process. Also, the numerous quality measurement results
of the quality help developers of the VoIP system to dimension or
tune their system to take optimal advantage of a codec. For
example, during network planning, operators can predict the
amount of bandwidth needed for high quality voice calls.
An adaptive VoIP application needs to know which quality is
achieved with a different codec parameters set to be able to make
an optimal selection of the codec parameters under varying
network conditions.
As suggested in [50] an RTP payload specification for an IIAC
codec should include a rate control. Similar to the performance
of the codec, the rate control unit has a big impact on the
overall quality of experience. Thus, it should be tested well
too.

o Software implementers need to verify whether their particular
codec implementation that might be optimized on a specific
platform confirms to the standard's reference implementation.
This is particularly important as some intellectual property
rights might only be granted, if the codec conforms to the
standard.
As the IIAC must not to be bit conform, which would allow simple
comparisons of correctness, other means of conformance testing
must be applied.
In addition, the standard conformance and interoperability of
multiple implementations must be checked.
Last but not least, implementers may implement optimized
concealment algorithms, jitter buffers or other algorithms. Those
algorithms have to be tested, too.

o Since the success of MP3, end users do acknowledge the existence
of a high quality codec. It would make sense to use the IIAC in a
brand marketing campaign (such as "Intel inside"). A quality
comparison between IIAC and other codecs might be part of the
marketing. Online testing with user participation might also
raise the awareness level.

All those stakeholders might have different requirements regarding
the codec's quality testing procedures. Thus, this document tries to
identify those requirements and shows which of the existing quality
measurement procedures can be applied to fulfill those specific
demands efficiently.

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In the following section we describe a primary optimization goal:
Quality of Experience (QoE). Next, we briefly list the most common
methods of how to perform subjective evaluations on speech and audio
quality. In Section 4, 5, and 6, we discuss on how to measure
complexity, latency, and bit- and frame rates. Section 7 describes
how other SDOs have measured the quality of their codecs. As
compared IIAC to previous standardized codecs, the IIAC is likely to
have different unique requirements and thus needs newly developed
quality testing procedures. To achieve this, in Section 8 we
describe the properties of Internet transmission paths. Section 9
summarizes the usage scenarios, for which the codec is going to be
used and finally, in Section 10, we recommend procedures on how to
test the IIAC.

2. Optimization Goal

The aim of the Codec WG is to produce a codec of high quality.
However, how can quality be measured? The measurement of the
features of a codec can be based on many different criteria. Those
include complexity, memory consumption, audio quality, speech
quality, and others. But in the end, it's the users' opinions that
really count since they are the customers. Thus, one important - if
not the most important quality measure of the IIAC - shall be the
Quality of Experience (QoE).

The ITU-T Standards ITU-T P.10/G.100 [22] defines the term "Quality
of Experience" as "the overall acceptability of an application or
service, as perceived subjectively by the end-user." The ITU-T
document G.RQAM [21] extends this definition by noting that "quality
of experience includes the complete end-to-end system effects
(client, terminal, network, services infrastructure, etc.)" and that
the "overall acceptability may be influenced by user expectations
and context".

These definitions already give guidelines on how to judge the
quality of the IIAC:

o The acceptability and the subjective quality impression of
endusers have to be measured (Section 3).

o The IIAC codec has to be tested as part of an entire
telecommunication system. It must be carefully considered whether
to measure the codec's performance just in a stand-alone setup or
to evaluate it as part of the overall system (Section 8).

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o The environments and contexts of particular communication
scenarios have to be considered and controlled because they have
an impact on the human rating behavior and on quality
expectations and requirements (Section 9).

3. Measuring Speech and Audio Quality

The perceived quality of a service can be measured by various means.
If humans are interrogated, those quality tests are called
subjective. If the tests are conducted by instrumental means (such
as an algorithm) they are called objective. Subjective tests are
divided up into formal and informal tests. Formal tests follow
strictly defined procedures and methods and typically include a
large number of subjects. Informal tests are less precise because
they are conducted in an uncontrolled manner.

3.1. Formal Subjective Tests

Formal subjective tests must follow a well-defined procedure.
Otherwise the results of multiple tests cannot be mutually compared
and are not repeatable. Most subjective testing procedures have been
standardized by the ITU.  If applied to coding testing, the testing
procedures follow the same pattern [26]:

"Performing subjective evaluations of digital codecs proceeds
via a number of steps:

o Preparation of source speech materials, including recording of
talkers;

o Selection of experimental parameters to exercise the features
of the codec that are of interest;

o Design of the experiment;

o Selection of a test procedure and conduct of the experiment;

o Analysis of results."

The ITU has standardized different formal subjective tests to
measure the quality of speech and audio transmission, which are
described in the following.

3.1.1. ITU-R Recommendation BS.1116-1

The ITU-R BS.1116-1 standard [14] is good for audio items with small
degradations (stimuli) and uses a continuous scale from

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imperceptible (5.0) to very annoying (1.0). It is a double blind
triple-stimulus with a hidden reference testing method and must be
done twice for the degraded sample and the hidden reference. In a 30
minutes session, 10-15 sample items can be judged. Overall, about 20
subjects shall rate the items. Testing shall take place with
loudspeakers in a controlled environment or with headphones in a
quiet room.

3.1.2. ITU-R Recommendation BS.1534-1 (MUSHRA)

The ITU-R BS.1534-1 standard [16] defines a method for the
subjective assessment of intermediate quality levels. Multiple audio
stimuli are compared at the same time. Maximal 12 but preferably
only 8 stimuli plus a hidden one with Hidden Reference and an anchor
are compared and judged. MUSHRA uses a continuous quality scale
(CQS) ranging from 0 to 100 divided into five equal intervals ("bad"
to "excellent"). In 30 minutes, about 42 stimuli can be tested.
Again, 20 test subjects shall rate the items with either headphones
or loudspeakers.

The standard recommends using as lower anchor a low-pass filtered
version with a bandwidth limit of 3.5 kHz. Additional anchors are
recommended, especially if specific distortions are to be tested.

3.1.3. ITU-T Recommendation P.800

The ITU-T P.800 defines multiple testing procedures to assess the
speech quality of telephone connections. The most important
procedure is called listening-only speech quality of telephone
connections. Listeners rate short groups of unrelated sentences. The
listeners are taken from the normal telephone-using population (no
experts). They use a typical sending system (e.g. a local telephone)
that may follow "modified IRS" frequency characteristics. The
results is the listening-quality scale, which is an absolute
category scale (ACS) ranging from excellent=5 to bad=1. Listeners
can judge about 54 stimuli within 30 minutes.

Other tests described in P.800 measure listening-effort, loudness-
preference scale, conversation opinion and difficulty,

3.1.4. ITU-T Recommendation P.805

The P.805 standard [24] extends P.800 and defines precisely how to
measure conversational quality. Subjects have to do conversation
tests to evaluate the communication quality of a connected. Expert,
experienced or untrained (naive) subjects have to do these tests

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collaboratively in soundproof cabinets. Typically, 6 transmission
conditions can be tested within 30 minutes. Depending on the
required precision, these tests have to be made 20 to 40 times.

3.1.5. ITU-T Recommendation P.880

To measure time-variable distortion, a continuous evaluation of
speech quality has been defined in P.880 [31]. Subjects have to
assess transmitted speech quality consisting of long speech
sequences with quality/time fluctuations. The quality is rated on a
continuous scale ranging from Excellent=5 to Bad=1 is dynamically
changed over the time while the stimuli are played. Stimuli have a
length of between 45 seconds and 3 minutes.

3.1.6. Formal Methods Used for Codec Testing at the ITU

In the last year, new narrow and wideband codecs have been tested
using ITU-T P.800 (and ITU-T P.830). For the ITU-T G.719 standard,
which supports besides speech content also audio, the ITU-R BS.1116-
1 testing method has been applied during the selection of potential
codec candidates. During the qualification phase, the method that
was used was the ITU-P BS.1584-1. For the ITU-T G.718 codec, the
Absolute Category Rating (ACR) following ITU-T P.800 has been
applied.

3.2. Informal Subjective Tests

Besides formal tests, informal subjective tests following less
stringent conditions might be taken to judge the quality of stimuli.
However, informal tests cannot be easily verified and lack the
reliability, accuracy and precision of formal tests. Informal tests
are needed if the available number of subjects who are able to
conduct the tests is low, or if time or money is limited.

3.3. Interview and Survey Tests

In ITU-T P.800 [23] and [9] interview and survey tests are
described. In P.800, it says that "if the rather large amount of
effort needed is available and the importance of the study warrants
it, transmission quality can be determined by 'service
observations'."

These service observations are based on statistical surveys common
in social science and marketing research. Typically, the questions
asked in a survey are structured.

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In addition, according to [23]: "To maintain a high degree of
precision a total of at least 100 interviews per condition is
required. A disadvantage of the service-observation method for many
purposes is that little control is possible over the detailed
characteristics of the telephone connections being tested."

3.4. Web-based Testing

If the large-wide scale proliferation of the Internet, researchers
suggested testing the speech or audio quality on web sites via web
site visitors [43]. A current web site that compares multiple audio
codecs has been setup at SoundExpert.org [42]. On this web site, a
user can download an audio item that consists of a reference item
and a degraded item. Then, the user must identify the reference and
rate the ODG of the degraded item. The tests are single-blind as the
user does not know which codec he is currently rating.

One can anticipate that the visitors of web sites will use similar
equipment for testing of audio samples and for conducting VoIP
calls. Thus, web site testing can be made realistic in a way that
considers the impact of (typically used) loudspeakers and

However, currently used web sites lack a proper identification of
outliers. Thus, all ratings of all users are considered despite the
fact that they might be (deliberately) faked or that subjects might
not be able to hear well the acoustic difference. Thus, one can
expect that web based ratings will show a high degree of variation
and that many more tests are needed to achieve the same confidence
that is gained within formal tests. A profound scientific study on
the quality of web based audio rating has not yet been published.
Thus, any statements on the validity of web based rating are
premature.

3.5. Call Length and Conversational Quality

In the ETSI technical report document ETR-250 [6], a model is
presented that discusses various impairments caused in narrow band
telephone systems. The ETSI model describes the combinatorial effect
of all those impairments. The ETSI model later became the famous E-
Model described in ITU-T G.107. Both the ETSI- and the E-Model
calculate the R factor that ranges from 0 (bad) to 100 (excellent
conversational quality).

Based on the R factor, the users' reaction to the voice transmission
quality of a connection can be predicted. For example, Section 8.3
describes the effect that users terminate the call if the quality is

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bad. More precisely, they summarize it as users who "(i) terminate
their calls unusually early, (ii) re-dial or even (iii) actually
complain to the network operator".

In the ETSI model, the percentage of users "terminating calls
early", TME, is given as

$TME=100\cdot erf\left(\frac{36-R}{16}\right)\%$

with $erf(X)$ being the sigmoid shaped Gaussian error function and
$R$ the R Factor of the E-Model (Figure 1). This relation is based
on results from "AT&T Long toll" interviews as cited in [2].

These findings have been confirmed by Holub et al. [12] who have
studied the correlation between call length and narrow band speech
quality. Birke et al. [1] have also studied the duration of phone
calls which show a duration varying with day time and day of the
week and also may be affected by pricing schemata.

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100 -+TME.                               +- 5
|..iii.                             |
T         |    .ii                            |
e         |      ii                        MOS|
r         |       i.                     .iiii|
m     80 -+       .i.                  .ii.   |
i         |        .i                .ii.     +- 4
n         |         i.              .i.       |      M
a         |         .i            .ii.        |      O
t         |          i.          .i.          |      S
e     60 -+          .i         .i.           |      |
|           i.       ii.            |      C
E         |           .i     .ii              +- 3   Q
a         |            i.   .i.               |      E
r     40 -+            .i  .i.                |
l         |             i..i.                 |
y         |             .ii.                  |
|            .il.                   |
(         |           .i..i                   +- 2
T     20 -+          .i.  i.                  |
M         |        .ii.   .i.                 |
E         |      .ii.      .i.                |
)         |    .ii.         .ii.              |
|MOSlii.           .iiiiiiiiiiiiiTME|
0 -+-----------------+-----------------+- 1
|                 |                 |
0                 50               100

R Factor

Figure 1 - Relation between calls terminating early, the R Factor,
and the speech quality given in (MOS-CQE)

Whereas bad quality is related to short calls, it remains unproven
whether better quality (>4 MOS) results in longer phone calls. There
are two factors which might have an opposite effect on the call
length. On the one hand, if the quality is superb, the talkers might
be more willing to talk because of the pleasure of talking, on the
other hand they might fulfill their conversational tasks faster
because of the great quality Thus, depending on the context, good
speech quality might result either in longer or shorter calls.

3.6. Field Studies

Field studies can be conducted if usage data on calls are collected.
Field studies are useful to monitor real user behavior and to
collect data about the actual conversational context.

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Because of highly varying conditions, the precision of those
measurements is high and many tests have to be done to get
significantly different measurement values. Also, the tests are not
repeatable because the conditions are changing with time.

For example, Skype has done quality tests in a deployed VoIP system
in the field with its users as testers [47]. The subjective tests
are done in the following manner.

o Download of test vectors to VoIP clients. Typically, this can be
done with an automated software update.

o Delivery changing VoIP configurations (such as the used codecs)
so that different calls are subjected to different
configurations. The selection of configurations can be done
randomly, alternating in time or based on other criteria.

o Collecting feedback from the users. For example, the following
parameters can be monitored or recorded:

o The call length and other call specific parameters

o A user's quality voting (e.g. MOS-ACR) after the call

o Other feedback of the user (e.g. via support channels)

The field tests have the benefit of being conducted under real
conditions with the real users. However, they have some drawbacks.
First, the experimental conditions cannot be controlled well.
Second, the tests are only valid for the current situations and do
not allow predictions for other use cases. Third, the statistical
significance might be largely questionable if confidence intervals
are overlapping.

The costs for running the tests are low because the users are doing
the tests for free. However, the operator might lose users after a
user experienced a test case causing bad quality.

3.7. Objective Tests

Objective tests, also called instrumental tests, try to predict the
human rating behavior with mathematical models and algorithms. They
also calculate quality ratings for a given set of audio items.
Naturally, they are not rating as precisely as their human
counterparts, whom they try to simulate. However, the results are
repeatable and less costly than formal subjective testing campaigns.
Instrumental methods have a limited precision. That means that their

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quality ratings do not perfectly match the results of formal
listening-only tests. Typically, the correlation between formal
results and instrumental calculations are compared using a
correlation function. The resulting metric is given as R ranging
from 0 (no correlation) to 1 (perfect match).

Over the last years, several objective evaluation algorithms have
been developed and standardized. We describe them briefly in the
following.

3.7.1. ITU-R Recommendation BS.1387-1

The ITU developed an algorithm that is called Perceptual Evaluation
of Audio Quality (PEAQ). It was published in the document ITU-R
BS.1387 called Method for objective measurements of perceived audio
quality in 1998 [15]. PEAQ is intended to predict the quality rating
of low-bit-rate coded audio signals. Two different versions of PEAQ
are provided: a basic version with lower computational complexity
and an advanced version with higher computational complexity.

PEAQ calculates a quality grading called "Objective Difference
Grade" (ODB) ranging from 0 to -4. Typically, it shows a prediction
quality of between R=0.85 and 0.97 when compared to subjective
testing results. The ITU-T Study Group 12 assumes that PEAQ can
detect auditable differences between two implementations of the same
codec [5].

3.7.2. ITU-T Recommendation P.862

The ITU-T PESQ algorithm [27] is intended to judge distortions
caused by narrow band speech codecs and other kind of channel and
transmission errors. These include also variable delays, filtering
and short localize distortions such as those caused by frame loss
concealment. For a large number of conditions, the validity and
precision of PESQ has been proven. For untested distortions, prior
subjective tests must be conducted to verify whether PESQ judges
these kinds of distortions precisely. Also, it is recommended to use
PESQ for 3.1 kHz (narrow-band) handset telephony and narrow-band
speech codecs only. For wide-band operations, a modified filter has
to be applied prior to the tests.

Furthermore, the ITU-T Recommendation P.862.1 [28] describes how to
transfer the PESQ's raw scores, which range from -0.5 to 4.5, to
MOS-LQO values similar to those gathered from ACR ratings. Then, as
it has been shown, the correlation between a large corpus of testing
samplings shows a correlation of R=0.879 (instead of R=0.876)
between subjective and MOS-LQO (respective PESQ raw) ratings. The

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ITU-T Recommendation P.862.2 [29] modifies the PESQ algorithm
slightly to support wideband operations. And finally, the ITU-T
Recommendation P.862.3 [30] gives detailed hints and recommendations
on how and when to use the PESQ algorithms.

3.7.3. ITU-T Draft P.OLQA

The soon-to-be standardized algorithm P.OLQA [40] extends PESQ and
will be able to rate narrow to super-wideband speech and the effect
of time-varying speech playout. Later distortions are common in
modern VoIP systems which stretch and shrink the speech playout
during voice activity to adapt it to the delay process of the
network.

4. Measuring Complexity

Besides audio and speech quality, the complexity of a codec is of
prime importance. Knowing the algorithmic efficiency is important
because:

.  the complexity has an impact on power consumption and system
costs

.  the hardware can be selected to fit pre-known complexity
requirements and

.  different codec proposals can be compared if they show similar
performances in other aspects.

Before any complexity comparisons can be made, one has to agree on
an objective, precise, reliable, and repeatable metric on how to
measure the algorithmic efficiency. In the following, we list three
different approaches.

4.1. ITU-T Approaches to Measuring Algorithmic Efficiency

Over the last 17 years, the ITU-T Study Group 16 measured the
complexity of codecs using a library called ITU-T Basic Operators
and described in ITU-T G.191 [19], which counts the kind and number
of operations and the amount of memory used. The latest version of
the standard supports both fix-point operations of different widths
and floating operations.  Each operation can be counted
automatically and weighted accordingly. The following source code is
an [edited] excerpt from the source file baseop32.h:

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/* Prototypes for basic arithmetic operators */

Word16 add (Word16 var1, Word16 var2);

/* Short sub,           1   */
Word16 sub (Word16 var1, Word16 var2);

/* Short abs,           1   */
Word16 abs_s (Word16 var1);

/* Short shift left,    1   */
Word16 shl (Word16 var1, Word16 var2);

/* Short shift right,   1   */
Word16 shr (Word16 var1, Word16 var2);

...

/* Short division,       18  */
Word16 div_s (Word16 var1, Word16 var2);

/* Long norm,             1  */
Word16 norm_l (Word32 L_var1);

In the upcoming ITU-T G.GSAD standard another approach has been used
as shown in the following code example. For each operation, WMPOS
functions have been added, which count the number of operations. If
the efficiency of an algorithm has to be measured, the program is
started and the operations are counted for a known input length.

for (i=0; i<NUM_BAND; i++)
{
#ifdef WMOPS_FX
move32();move32();
move32();move32();
#endif
state_fx->band_enrg_long_fx[i] = 30;
state_fx->band_enrg_fx[i] = 30;
state_fx->band_enrg_bgd_fx[i] = 30;
state_fx->min_band_enrg_fx[i] = 30;
}

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4.2. Software Profiling

The previously described methods are well-established procedures on
how to measure computational complexity. Still, they have some
drawbacks:

o Existing algorithms must be modified manually to include
instructions that count arithmetic operations. In complex codecs,
this may take substantial time.

o The CPU model is simple as it does not consider memory access
(e.g. cache), parallel executions, or other kinds of optimization
that are done in modern microprocessors and compilers. Thus, the
number of instructions might not correlate to the actual
execution time on modern CPUs.

Thus, instead of counting instructions manually, run times of the
codec can be measured on a real system. In software engineering,
this is called profiling. The Wikipedia article on profiling [54]
explains profiling as follows:

"In software engineering, program profiling, software profiling or
simply profiling, a form of dynamic program analysis (as opposed
to static code analysis), is the investigation of a program's
behavior using information gathered as the program executes. The
usual purpose of this analysis is to determine which sections of a
program to optimize - to increase its overall speed, decrease its
memory requirement or sometimes both.

o  A (code) profiler is a performance analysis tool that, most
commonly, measures only the frequency and duration of
function calls, but there are other specific types of
profilers (e.g. memory profilers) in addition to more
comprehensive profilers, capable of gathering extensive
performance data

o  An instruction set simulator which is also - by necessity - a
profiler, can measure the totality of a program's behaviour
from invocation to termination."

Thus, a typical profiler such as the GNU gprof can be used to
measure and understand the complexity of a codec implementation.
This is precisely the case because it is used on modern computers.
However, the execution times depend on the CPU architecture, the PC
in general, the OS and parallel running programs.

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To ensure repeatable results, the execution environment (i.e. the
computer) must be standardized. Otherwise the results of run times
cannot be verified by other parties as the results may differ if
done under slightly changed conditions.

4.3. Cycle Accurate Simulation

If reliable and repeatable results are needed, another similar
approach can be chosen. Instead of run times, CPU clock cycles on a
virtual reference system can be measured. Quoting Wikipedia again
[52]:

"A Cycle Accurate Simulator (CAS) is a computer program that
simulates a microarchitecture cycle-accurate. In contrast
an instruction set simulator simulates an Instruction Set
Architecture usually faster but not cycle-accurate to a specific
implementation of this architecture."

With a cycle accurate simulator, the execution times are precise and
repeatable for the system that is being studied. If two parties make
measurements using different real computers, they still get the same
results if they use the same CAS.

A cycle accurate simulator is slower than the real CPU by a factor
of about 100. Also, it might have a measurement error as compared to
the simulated, real CPU because the CPU is typically not perfectly
modeled.

If an x86-64 architecture shall be simulated, the open-source Cycle
accurate simulator called PTLsim can be considered [55]. PTLsim
simulates a Pentium IV. On their website, the authors of PTLsim
write:

"PTLsim is a cycle accurate x86 microprocessor simulator and
virtual machine for the x86 and x86-64 instruction sets. PTLsim
models a modern superscalar out of order x86-64 compatible
processor core at a configurable level of detail ranging from
full-speed native execution on the host CPU all the way down
to RTL level models of all key pipeline structures."

Another cycle accurate simulator called FaCSIM simulated the ARM9E-S
processor core and ARM926EJ-S memory subsystem [36]. It is also
available as open-source. Texas Instruments also provides as CAS for
its C64x+ digital signal processor [44].

To have a metric that is independent of a particular architecture,
the results of cycle accurate simulators could be combined.

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4.4. Typical run time environments

The IIAC codec will run on various different platforms with quite
diverse properties. After discussions on the WG mailing list, a few
typical run time environments have been identified.

Three of the run time environments are end devices (aka phones). The
first one is a PC, either stationary or a portable, having a >2 GHz
PCU, >2 GByte of RAM, and a hard disk for permanent storage.
Typically, a Windows, MacOS or Linux operating system is running on
a PC. The second one is a SmartPhone, for example with an ARM11 500
MHz CPU, 192 Mbyte RAM and 256 MByte Flashrom. An example is the HTC
Dream Smart phone equipped with Qualcomm MSM7201A chip. Various
operating systems are found on those devices such as Symbian,
Android, and iOS. The last ones are high end stationary VoIP phones
with for example a 275-MHz MIPS32 CPU (with 400 DMIPS) with a 125-
MHz (250 MIPS) ZSP DSP with dual-MAC. They both have more than 1
Mbyte RAM and FlashRom. An exemplary Chip is the BCM1103 [3].

Besides phones, VoIP gateways are frequently needed for conferencing
or transcoding to legacy VoIP or PSTN. In this case, two different
platforms have been identified. The first one is based on standard
PC server platforms. It consists, for example, of an Intel six core
Xeon 54XX or 55XX, two 1 GB NIC, 12 GByte RAM, hard disks, and a
Linux operating system. Thus, a server can serve from 400 to 10000
calls depending on conference mode, codecs used, and ability of user
pre-encoded audio [46]. On the other hand, high density, highly
optimized voice gateways use a special purpose hardware platform
like for example, TNETV3020 chips consisting of six TI C64x+ DSPs
with 5.5 MB internal RAM. If they run with a Telogy conference
engine, they might serve about 1300 AMR or 3000 G.711 calls per chip
[45].

5. Measuring Latency

Latency is a measure of time delay experienced in a system. Latency
can be measured as one-way delay or as round-trip time. The latter
one is the one-way latency from a source to destination plus the
one-way latency back from destination to source. Latency can be
measured at multiple positions, at the network layer or at higher
layers [53].

As we aim to increase the Quality of Experience, the mouth-to-ear
delay is of importance because it directly correlates with
perceptual quality [17]. More precisely, the acoustic round-trip
time shall be a means of optimization when studying interactive and
conversational application scenarios.

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5.1. ITU-T Recommendation G.114

The G.114 standard [45] gives guidelines on how to estimate one-way
transmission delays. It describes how the delay introduced by the
codec is generated. Because most of the encoders do a processing of
frames, the duration of a frame (named "frame size") is the foremost
contributor to the overall algorithmic delay. Citing [18]:

"In addition, many coders also look into the succeeding frame to
improve compression efficiency. The length of this advance look is
known as the look-ahead time of the coder. The time required to
process an input frame is assumed to be the same as the frame
length since efficient use of processor resources will be
accomplished when an encoder/decoder pair (or multiple
encoder/decoder pairs operating in parallel on multiple input
streams) fully uses the available processing power (evenly
distributed in the time domain). Thus, the delay through an
encoder/decoder pair is normally assumed to be:"

$2*frameSize + lookAhead$

might contribute significantly to the codec delay.

Also, if IP transmissions are used and multiple frames are
concatenated in one IP packet, further delay is added. Then, "the
minimum delay attributable to codec-related processing in IP-based
systems with multiple frames per packet is:"

$(N+1)*frameSize + lookAhead$

"where N is the number of frames in each packet."

5.2. Discussion

Extensive discussion on the WG mailing list led to the insight that
the afore mentioned ITU delay model overestimates the delay
introduced by the codec. In the last decade, two developments led to
slightly other conditions.

First, the processing power of CPU increased significantly (see
Section 4.4). Nowadays, even stand-alone VoIPs have CPUs with a
speed of 300 MHz. They are capable of doing the encoding and
decoding faster than real time. Thus, also the delay introduced by
processing is not at 100% anymore but significantly lower. For
example, it might be just 10% or less.

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Second, even if the CPUs are fully loaded, especially if also other
tasks such as a video conference or other calls need to be
processed, advantaged scheduling algorithms allow for a timely
encoding and decoding. For example, a staggered processing schedule
can be used to reduce processing delays [45].

Thus, the impact of processing delay is reduced significantly in
most of the cases.

Moreover, besides a look-ahead time, the decoder might also
contribute to the algorithmic delay e.g. if decoded and concealed
periods shall be mixed well.

6. Measuring Bit and Frame Rates

For decades, there was a quest to achieve high quality while keeping
the coding rate low. Coding rate, sometimes called multimedia bit
rate, is the bit rate that an encoder produces as its output stream.
In cases of variable rate encoding, the coding bit rate differs over
time. Thus, one has to describe the coding rate statistically. For
example, minimal, mean, and maximal coding rates need to be
measured.

A second parameter is the frame rate as the encoder produces frames
at a given rate.  Again, in case of discontinuous transmission modes
(DTX), the frame rate can vary and a statistical description is
required.

Both coding and frame rate influence network related bit rates. For
example, the physical layer gross bit rate is the total number of
physically transferred bits per second over a communication link,
including useful data as well as protocol overhead [51]. It depends
on the access technology, the packet rate, and packet sizes. The
physical layer net bit rate is measured in a similar way but
excludes the physical layer protocol overhead. The network
throughput is the maximal throughput of a communication link of an
access network. Finally, the goodput or data transfer rate refers to
the net bit rate delivered to an application excluding all protocol
avoid packet losses or queuing delay, the goodput shall be equally
large as the coding rate.

The relation between goodput and the physical layer gross bit rate
is not trivial.  First of all, the goodput is measured end-to-end.
The end-to-end path can consist of multiple physical links, each

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utilization and link quality. Third, packets may be tunneled through
Fourth, IP header compression might be applied (as in LTE networks)
the network connection must be collected to predict what the
relation between physical layer gross bit rate and a given coding
and frame rate is going to be. Applications, which have only a
limited view of the network, can hardly know the precise relation.

For example, the DCCP TFRC-SP transport protocol simply estimates a
header size on data packets of 36 bytes (20 bytes for the IPv4
numbers) [7][8]. Thus, [11] suggested a typical scenario in which
one encoded frame is transmitted with the RTP, UDP, IPv4 and IEEE
802.3 protocols and thus each packet contains packet headers having
12 bytes, 8 bytes, 20 bytes and 18 bytes respectively. The gross bit
rate calculates as

$r_{gross}=r_{coding}+overhead \cdot framerate$

where $r_{coding}$ is the coding rate of the encoding, $framerate$
is the frame rate of the codec, $overhead$ is the number of bits for
protocol headers in each packet (typically 58*8=464), and the
$r_{gross}$ is the rate used on physical mediums.

7. Codec Testing Procedures Used by Other SDOs

To ensure quality, each newly standardized codec is rigorously
tested. ITU-T Study Group 12 and 16 have developed very good and
mature procedures on how to test codecs. The ITU-T Study Group 12
has described the testing procedures of narrow- and wide-band codecs
in the ITU-T P.830 standard.

7.1. ITU-T Recommendation P.830

The ITU-T P.830 recommendation describes methods and procedures for
conducting subjective performance evaluations of digital speech
codecs. It recommends for most applications the Absolute Category
Rating (ACR) method using the Listening Quality scale. The process
of judging the quality of a speech codec consists of five steps,
which are described in the following.

Step 1: Preparation of Source Speech Materials Including Recording
of Talkers. When testing a narrow band codec, the recommendation
suggests to use a bandwidth filter before applying sample items to a
codec. This bandwidth filter is called modified Intermediate
Reference System (IRS) and limits the frequency band to the range

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between 300 and 3400 Hz. In addition, the recommendation states that
"if a wideband system (100-7000 Hz) is to be used for audio-
conferencing, then the sending end should conform to IEC Publication
581.7."

It also says that "speech material should consist of simple, short,
meaningful sentences." The sentences shall be understandable to a
broad audience and sample items should consist of two or three
sentences, each of them having a duration of between 2 and 3
seconds. Sample items should not contain noise or reverberations
longer than 500 ms. The recommendation also makes suggestions on the
loudness of the signal: "A typical nominal value for mean active
speech level (measured according to Recommendation P.56) is
-20 dBm0, corresponding to approximately -26 dBov"

Step 2: Selection of Experimental Parameters to Exercise the
Features of the Codec That Are of Interest. Various parameters shall
be tested. Those include

o Codec Conditions

o  Speech input levels ("input levels of 14, 26 and 38 dB below
the overload point of the codec")

o  Listening levels ("levels should lie 10 dB to either side of
the preferred listening level")

o  Talkers

. Different talkers ("a minimum of two male and two female
talkers")

. Multiple talkers ("multiple simultaneous voice input
signals")

o  Errors ("randomly distributed bit errors" or burst-errors)

o  Bitrates ("The codec must be tested at all the bit rates")

o  Transcodings ("Asynchronous tandeming", "Synchronous
tandeming", and "Interoperability with other speech coding
standards")

o  Mismatch (sender and receiver operate in different modes)

o  Environmental noise (sending) ("30 dB for room noise" and "10
dB and 20 dB for vehicular noise")

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o  Network information signals ("signaling tones, conforming to
Recommendation Q.35, should be tested subjectively, and the
minimum should be proceed to dial tone,  called subscriber
ringing tone, called subscriber engaged tone, equipment
engaged tone, [and] number unobtainable tone.")

o  Music ("to ensure that the music is of reasonable quality")

o Reference conditions ("for making meaningful comparisons")

o  Direct (no coding, only input and output filtering)

o  Modulated Noise Reference Unit (MNRU)

o  Signal-to-Noise Ratio (SNR) (for comparison purposes)

o  Reference codecs

Step 3: Design of the Experiment. The considerations described in
B.3/P.80 apply here. Typically, it is not possible to test each
combination of parameters. Thus, recommendation P.830 states that
"it is recommended that a minimum set of experiments be conducted,
which, although they would not cover every combination, would result
in sufficient data to make sensible decisions. [...] Extreme caution
should be used when comparing systems with widely differing
degradations, e.g. digital codecs, frequency division multiplex
systems, vocoders, etc., even within the same test."

Step 4: Selection of a Test Procedure and Conduct of the Experiment.
Here, the considerations as in B.4/P.80 apply. However, a modified
IRS at the receiver shall be used (narrow band) or an IEC
Publication 581.7 filter (wideband). Also, "Gaussian noise
equivalent to -68 dBmp should be added at the input to the receiving
system to reduce noise contrast effects at the onset of speech
utterances."

Step 5: Analysis of Results. Again, the considerations detailed in
B.4.7/P.80 apply. The arithmetic mean (over subjects) is to be
calculated for each condition at each listening level.

7.2. Testing procedure for the ITU-T G.719

Recently, the ITU-T has standardized the audio and speech codec ITU-
T G.719. The G.719 has similar properties as the anticipated IIAC,
thus the optimization and characterization of the G.719 is of
particular interest.

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In the following, we will describe the "Quality Assessment Test
Plan" in TD 322 and 323 [33][35]. The ITU Study Group 16 used ITU-R
BS.1116 to tests sample items. Audio sample items were sampled at 48
kHz mixed down to mono. Speech sample items contain one sentence
with a duration of 4 s, mixed content had a duration of 5-6 s and
music a duration of between 10 and 15 s. The beginning and ending of
the samples were smoothed. Also, a filter was applied to limit the
nominal bandwidth of the input signal to the range of 20 to 20000
(including a jingle) have been selected. For music items, classical
and modern styles of music have been selected. Besides the codec
under test, test stimuli degraded with LAMP MP3 and G722 were added
to the tests. Some test stimuli have been modified to include
reverberations or an interfering talker and office noise. Some tests
were done studying the effect of a frame erasure rate of 3% having
random loss patterns. All listening labs used different sample items
and attention paid to not use the same material twice.

Listening labs were required to provide the results of 24
experienced listeners excluding those listeners, who did not passed
a pre- and post-screening. The experienced listeners should "neither
have a background in technical implementations of the equipment
under test nor do they have detailed knowledge of the influence of
these implementations on subjective quality".

During the tests, "circum aural headphones - open back for example:
STAX Signature SR-404 or Sennheiser HD-600) on both ears (diotic
presentation)" were used. The listening levels were -26 dB relative
to OVL.

Some results of the listening tests are given in TD 341 R1 [34]. In
those tests, they also compared the subjective ratings that were
made following BS.1116 with the objective ratings of ITU-R BS.1387-
1. The correlation between objective and subjective ratings was
below R=0.9.

8. Transmission Channel

Between speech encoder and decoder lies a transmission channel that
effects the transmission. For cellular or wireless phones, the
typical transmission channel is assumed to be equal to the wireless
(e.g., in GSM, UMTS, DECT). The bandwidth is typically constant in
DECT and GSM or variable in a given range depending on the quality
of the wireless transmission (UMTS). Bit errors do occur but they
don't be equally distributed if unequal bit error correction is
applied (UMTS).

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In the case of the IIAC codec, the transmission channel is the
internet. More precisely, it is the packet transmission over the
Internet, plus the transport protocol (e.g. UDP, TCP, DCCP), plus
potentially Forward Error Correction, and plus dejittering buffers.

Also, the transmission channel is reactive. It changes its
properties depending on how much data is transmitted. For example,
parallel TCP flows reduce their transmission bandwidth in the
presence of an unresponsive UDP stream.

Overall, one can say that the transmission channel "Internet" is
difficult to understand. Thus, in this chapter, we try to shed light
on the question of what types of transmission channels a codec has
to cope with.

8.1. ITU-T G.1050: Network Model for Evaluating Multimedia Transmission
Performance over IP (11/2007)

The current ITU-T G.1050 standard [20] describes layer 3 packet
transmission models that can be used to evaluate IP applications.
The models are of statistical nature. They consider networks
architectures, types of access links, QoS controlled edge routing,
MTU size, networks faults, link failures, route flapping, reordered
packets, packet loss, one-way delay, variable deploys and background
traffics.

G.1050 is a network model consisting of three parts, LAN a, LAN b,
and an interconnection core. Both LANs can have different rates and
occupancy and can be of different types. LAN and core are connected
via access technologies, which might vary in data rate, occupancy
and MTU size.

The core is characterized by route flapping, link failures, one-way
delay, jitter, packet loss and reordered packets. Route flaps are
repeatedly changed in a transmission path because of alternating
routing tables. These routing updates cause incremental changes in
the transmission delays. A link failure is a period of consecutive
packet loss. Packet losses can be bursty having a high loss rate
during bursts and having otherwise a lower loss rate otherwise.
Delays are modeled via multiple different jitter models supporting
delay spikes, random jitter and filtered random jitters.

The standard recommends three profiles, named "Well-managed IP
network", "Partially-managed IP network", and "Unmanaged IP Network,
Internet", which differ in their connection qualities.

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Limitations to these models are the missing cross-correlation
between packet delays and packet loss events, the lack of
responsiveness to the tests application flow, and the lack of link
qualities that vary with time.

8.2. Draft G.1050 / TIA-921B

Currently, an enhancement to ITU-T G.1050 (11/2007) is being
developed (e.g. [13])). It does not use a statistical model but
takes advantage of the NS/2 simulator. Thus, most of the above
mentioned limitations have been overcome.

Despite that, even the new model does not yet give an answer to the
question of which distributions of typical Internet connection
qualities can be expected.

8.3. Delay and Throughput Distributions on the Global Internet

In general, it is not precisely known how the qualities of end-to-
end connections are distributed. It is also unclear whether the
anticipated IIAC Codec will be used globally or whether its area of
usage will be somehow restricted.

Despite the fact, that the codec has to be optimized for an unknown
Internet, the following scientific publications give an estimate on
how different Internet end-to-end paths might behave. One recent
access traffic of a major European ISP [37].

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+------------------------------------------------------------+
p 0.6-+                                                            |
r     |  e eDonkey                                                 |
o     |                           ee                               |
b     |  H HTTP                   e e                              |
a     |                          ee e                              |
b     |                          e  e                              |
i 0.4-+                          e   e                             |
l     |                          e   e                             |
i     |                         e    e                             |
t     |                         e    e     HHHH                    |
y     |                         e     e  HHHHHHHHH                 |
|                        ee     e HH       HH                |
d 0.2-+                        e      eHH         HH               |
e     |                        e       H           HH              |
n     |                       ee      He            HH             |
s     |            ee         e      HH e            HH            |
i     |           e  ee      e     HH    e            HHH          |
t     |         ee     eeeeee HHHHHH      eeee          HHH        |
y 0.0-+ eHeHeHeHHHHHHHHHHHHHHH                eeeeeeeeeeeeeHHHHHHH |
+----+---------+---------+--------+---------+---------+------+
|         |         |        |         |         |
0.1       1.0       10       100      1000      10000

Throughput [kbps]

Figure 2 Achieved throughput of flows measured for eDonkey and HTTP
applications [37]

Figure 2 displays the throughput distribution of TCP connections for
eDonkey peer-to-peer and HTTP applications. It only considers single
flow with a length of more than 50 Kbyte. But typically, a web
browser uses two to three TCP connections at the same time and an
eDonkey client about 10. Still, the throughput of a single HTTP flow
is in about an order faster than the of eDonkey flow. In [37], the
authors assume this is due to the fact that peer-to-peer connections
fill the uplink and that HTTP is used at the faster downlink.

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+------------------------------------------------------------+
|                                                            |
|                    **                                      |
p 0.8-+                    **                                      |
r     |                    ***                                     |
o     |                    * *                                     |
b     |                   ** *                                     |
a 0.6-+                   *  *                                     |
b     |                   *  **                                    |
i     |                   *   *                                    |
l     |                   *   *                                    |
i     |                   *   *                                    |
t 0.4-+                  **   **                                   |
y     |                  *     *                                   |
|                  *      * ****                             |
d     |                  *       *    *                            |
e 0.2-+                  *            **                           |
n     |                 **             **                          |
s     |            **** *               ***                        |
i     |          ***  ***                 ***                      |
t     |        ***                          **************         |
y 0.0-+*********                                  *****************|
+-------+-----------------+----------------+-----------------+
|                 |                |                 |
10                100             1000            10000

RTT [ms]

Figure 3 TCP roundtrip times [36]

Figure 3 displays TCP roundtrip times including both access and
backbone network. Both graphs can be seen as an indication for the
assumption that an application, even in modern Internet access
networks, might be subjected to a wide variability of throughput
ranging from a few kbits/s up to 10 Gbit/s and TCP round trip times
from 5ms up to one of several seconds.

Albeit these results are only valid for TCP, similar results should
be expected for RTP over UDP - with a small advantage because UDP
flows are not always responsive.

As a summary, a codec for the Internet should be able to work under
these widely varying transmission conditions and should be tested
against a wide distribution of expected throughputs.

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8.4. Transmission Variability on the Internet

Besides effects such as route flapping or link failures modeled in
G.1050 [20], the Internet experience in short-time scales sharp
changes sharply in bandwidth utilization. For example, [49] and [38]
showed that variability of Internet traffic comes in form of spike
like traffic increments. Similarly, [32] studied why the Internet is
bursty in time scales of between 100 and to 1000 milliseconds.

In the light of these results, one can assume that the IIAC's
transmission conditions will vary in similar time scales. More
precisely, it will be subjected to

.  variability due to bursty traffic having a duration of between
100 and 1000 milliseconds,

.  interruptions due to temporal link failures every minute to every
hour that might have a temporal interruption from 64 ms to
several seconds [20], and

.  route flap events every minute to every hour that have a delay of
between 2 and 128 ms [20].

8.5. The Effects of Transport Protocols

Realtime multimedia is not always transported over RTP and UDP.
Sometimes it makes sense to use a different transport protocol or an

.  If a scalable codec shall be supported, RTCP-based feedback
information can be utilized to implement a rate control
mechanisms [41]. However, RTCP-based feedback suffers from the
drawback that RTCP messages are allowed only every 5 s. Thus,
implementing a fast responding mechanism is not possible.

.  In the presence of restricted firewalls, VoIP can sometimes only
be transmitted over TCP. In those cases, the transmission
scheduling is not given by the codec but by TCP. TCP algorithms
typically don't have a smooth sending rate but frequently send
packets in bursts and change the amount of packets sent every
round trip time (Figure 4). More precisely, TCP causes the
sending schedule to behave in the following way:

.  During the Slow Start phase (for example at the beginning of
a TCP connection) the transmission rate increases
exponentially.

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.  If a TCP segment is not acknowledged after about four RTTs,
the TCP sending rate starts at one packet per RTT again.

.  During congestion avoidance, the sending rate increases
steadily by one segment per RTT.

.  If a congestion event is then detected, the sending rate is
reduced by 50%.

p 15-+-------------------------------------------------------------+
a    |                                                             |
c    |             **                  **              **          |
k    |           ** *                ** *            ** *          |
e    |         **   *              **   *          **   *          |
t    |       **     *            **     *        **     *        **|
s    |     **       *          **       *      **       *      **  |
8-+   **         *        **         *    **         *    **    |
p    |   *          *      **           *  **           *  **      |
e    |   *          *      *            ***             ***        |
r    |   *          *      *                                       |
4-+  *           *     *                                        |
R    |  *           *     *                                        |
T  2-+ *            *    *                                         |
T  1-+*             *   *                                          |
+---------+---------+---------+---------+---------+---------+-+
|         |         |         |         |         |         |
0        10        20        30        40        50        60

time in round- trip times (RTT)

Figure 4 Sending rate of a standard TCP over time

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.  The DCCP transport protocol supports multiple congestion control
protocols and gives means to support TCP friendliness without
retransmission. Thus, it is suitable for real time multimedia
transmissions. DCCP supports a TCP emulation, which shows a
similar rate over time as TCP, and the TFRC congestion control,
which changes its rate in a smoother way (Figure 5).
Besides TFRC, which is intended to transmit packets of maximal
size (aka MTU), TFRC-SP is optimized for flows with variable
packet sizes such as VoIP. With TFRC-SP, smaller packets can be
transmitted at a faster pace than it is the case for larger
packets because they contribute less to the gross bandwidth
consumption.
The TFRC protocol might provide a lower bandwidth and a lower QoE
as UDP or TCP, unless if not proper optimizations are taken (see
[48]). Also, it is suggested to limit the rate control to 100
packets per second. This limit might be too low for an IIAC.

p 15-+-------------------------------------------------------------+
a    |                                                             |
c    |             **                  **                  **      |
k    |           **  **              **  **              **  **    |
e    |         **      **          **      **          **      **  |
t    |       **          **      **          **      **          **|
s    |     **              **  **              **  **              |
8-+   **                  **                  **                |
p    |   *                                                         |
e    |   *                                                         |
r    |   *                                                         |
4-+  *                                                          |
R    |  *                                                          |
T  2-+ *                                                           |
T  1-+*                                                            |
+---------+---------+---------+---------+---------+---------+-+
|         |         |         |         |         |         |
0        10        20        30        40        50        60

time in round- trip times (RTT)

Figure 5 Sending rate of the TFRC protocol

In general, the transport protocol has a clear influence on the
transmission conditions. Coding rates need to be adapted by sharply
and smoothly to changed bandwidth estimations. Changes of the
bandwidth estimation may occur every RTT. Also, in cases of a TCP
timeout, the transmission is halted and the decoding must be
stalled.

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8.6. The Effect of Jitter Buffers and FEC

Both jitter buffers trade frame losses against delay. In cases of a
jitter buffer, frames are delayed before playout. This helps in
cases of lately arriving frames that would otherwise be ignored and
would have to be concealed. Jitter buffers are adaptive and are
changing dynamically to the current loss process on the Internet.

Forward Error Correction helps to cope with isolated losses as
redundant speech frames are transmitted in the following packets. In
the presence of loss, FEC increases the delay because the receiver
has to wait for the following packets. Both delay and packet losses
are important contributors to the overall Quality of Experience [2].

Since the delay process on the Internet often comes in the form of a
gamma distribution, thus a statistical monitor of past delays helps
to predict the size of future jitter. Then, if the playout schedule
does not match the predicted loss process, playout can be
accelerated or slowed down.

However, due to the reasons described in Section 8.4 not all
increments in transmission time might be predictable. This has a
profound effect on the jitter buffer as it actually cannot predict
well, whether a frame is lost or whether it is going to be delayed.
If a frame is scheduled for playout but has not been received, the
jitter buffer has to consider two cases. First, the frame is lost
and has to be concealed. This typically means that the audio signal
needs to be extrapolated or interpolated to conceal the gap due to a
lost frame. Second, the frame is delayed and shall be played out at
a later point in time. Then, the resulting gap in playout must be
concealed by extrapolating the previous audio signal.

These issues have an effect on testing the concealment algorithm of
the codec. The same concealment function must be tested against time
gap concealment and loss concealment.

8.7. Discussion

Judging a codec performance using a realistic model of a
transmission channel is difficult. Good models of IP transmission
channels are available. However, before a codec can be tested
against those channels, further building blocks such as the
transport protocol, the jitter buffer, and FEC should be known - at
least roughly.

Alternatively, a codec can be tested only against of packet loss
patterns only without considering any rate adaption or playout

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rescheduling. But then again, the codec should be additionally
tested for those impairments, which occur due to the dynamics of the
Internet. These include

o slowing down and speeding up the playout in cases of moderate
rescheduling of playout times,

o stalling and resuming the playout in cases of temporal link
outages,

o moderately reducing and increasing bit and frame rates during
contention periods, and

o sharply reducing (in case of congestion) and fast increasing
(during connection establishment) of bit and frame rates.

o Time gap and loss concealment.

o Speeding up and slowing down the playout speed.

9. Usage Scenarios

Quality of Experience is the service quality perceived subjectively
by end-users (refer to Section 2) and as ITU-T document G.RQAM [21]
states "overall acceptability may be influenced by user expectations
and context". Thus, in this section we describe the usage scenarios,
in which the IIAC codec will probably be used, and the expectations
users have in those communication contexts. We list seven main
scenarios and describe their quality requirements.

9.1. Point-to-point Calls (VoIP)

The classic scenario is that of the phone usage to which we will
refer in this document as Voice over IP (VoIP). Human speech is
transmitted interactively between two Internet hosts. Typically,
besides speech some background noise is present, too.

The quality of a telephone call is traditionally judged by
subjective tests such as those described in [24]. The ACR scale used
in MOS-LQS sometimes might not be very suitable for high quality
calls, then - for example - the MUSHRA [16] rating can be applied.

A telephone call is considered good if it has a maximal mouth-to-ear
delay of 150 ms [17] and a speech quality of MOS-LQS 4 or above.
However, interhuman communication is still possible if the mounth-
to-ear delay is much larger.

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The effect of delay jitter might not be very well notable in case of
speech. Thus, playout rescheduling can happen often take place.

In many cases, phone calls are made between mobile devices such as
mobile phones and cellular phone. In these cases, energy consumption
is crucial and both complexity and transmission rate may be reduced
to save resources.

9.2. High Quality Interactive Audio Transmissions (AoIP)

In this scenario we consider a telephone call having a very good
audio quality at modest acoustic one-way latencies ranging from 50
and 150 ms [17], so that music can be listened to over the telephone
while two persons are talking interactively.

While delay expectations might be similar to those of classic
telephony, the audio quality must meet similar standards as those of
consumer Hifi equipment like MP3 and CD players, iPods, etc.

If music is played, playout rescheduling events may be heard easily
be heard as the rhythm changes. Only a few studies such as [10] have
been made to examine the effect of time varying delays on service
quality. In general, it can be assumed that the requirements
regarding constancies of playout schedules are higher than in case
of speech because human beings can notice rhythmic changes easily.
Thus, in the presence of music, frequent playout rescheduling shall
be avoided.

9.3. High Quality Teleconferencing

Also, for today's teleconferencing and videoconferencing systems
there is a strong and increasing demand for audio coding providing
the full human auditory bandwidth of 20 Hz to 20 kHz. This rising
demand for high quality audio is due to the following reasons:

o Conferencing systems are increasingly used for more elaborated
presentations, often including music and sound effects which
occupy a wider audio bandwidth than that of speech. For example,
Web conferences such as WebEx, GoToMeeting, Adobe Acrobat Connect
are based on an IP based transmission.

o The new "Telepresence" video conferencing systems, providing the
user with High Definition video and audio quality, create the
experience of being in the same room by introducing high quality
media delivery (such as from Cisco).

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o The emerging Digital Living Rooms are to be interconnected and
might require a constant high quality acoustic transmission at
high qualities.

o Spatial audio teleconference solutions increase the quality
because they take advantage of the cocktail-party effect. By
taking advantage of 3D audio, participants can be identified by
their location in a virtual acoustic environment and multiple
talkers can be distinguished from each other. However, these
systems require stereo audio, if the spatial audio is rendered

9.4. Interconnecting to Legacy PSTN and VoIP (Convergence)

This scenario does not include the use case of using a VoIP-PSTN
gateway to connect to legacy telephone systems. In those cases, the
gateway would make an audio conversion from broadband Internet voice
to the frugal 1930's 3.1 kHz audio bandwidth.

The quality requirements in this scenario are low because legacy
PSTN typically uses narrow-band voice. Also, in those cases one
might expect the codec negotiation might decide on a common codec
both for PSTN and VoIP in order to avoid transcoding.

However, the complexity requirements might be stringent because
central media gateways must scale to a high number of users. In this
context, hardware costs are an important criterion and the codec has
to operate efficient.

9.5. Music streaming

Music streaming typically does not require low delays. However, in
special cases such as live events and in the presence of alternative
transmission technologies, low-delay streaming may be demanded.

Examples are important sport events, which are streamed both on
terrestrial, (analogue) and low delay broadcast networks and on IP-
based distribution networks. The latter ones becomes aware (such as
when a footballer scores) more lately than the ones their neighbors
using terrestrial technology.

9.6. Ensemble Performances over a Network

In some usage scenarios, users want to act simultaneously and not
just interactively. For example, if persons sing in a chorus, if
musicians jam, or if e-sportsmen play computer games in a team
together they need to communicate acoustically.

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In this scenario, the latency requirements are much harder than for
interactive usages. For example, if two musicians are placed more
than 10 meters apart, they can hardly stay synchronized. Empirical
studies [10] have shown that if ensembles play over networks, the
optimal acoustic latency is at around 11.5 ms with a targeted range
from 10 to 25 ms.

Also, the users demand very high audio quality, very low delay and
very few events of playout rescheduling.

9.7. Push-to-talk like Services (PTT)

In spite of the development of broadband access (xDSL), a lot of
users do only have service access via PSTN modems or mobile links.
Also, on these links the available bandwidth might be shared among
multiple flows and is subjected to congestion. Then, even low coding
rates of about 8 kbps are too high.

If transmission capacity hardly exists, one can still degrade the
quality of a telephone call to something like a push-to-talk (PTT)
like service having very high latencies. Technically, this scenario
takes advantage of bandwidth gains due to disruptive transmission
(DTX) modes and very large packets containing multiple speech frames
causing a very low packetization overhead.

The quality requirements of a push-to-talk like service have hardly
been studied. The OMA lists as a requirement of a Push-to-talk over
cellular service a transmission delay of 1.6 s and a MOS values of
above 3.0 that typically should be kept [39]. However, as long as an
understandable transmission of speech is possible, the delay can be
even higher. For example, [39] allows a delay of typically up to 4 s
for the first talk-burst. Also, [39] describes a maximum duration of
speaking. If a participant speaking reaches the time limit, the
participant's righttospeak shall be automatically revoked.

If the quality of a telephone call is very low, then instead of
listening-only speech quality the degree of understandability can be
chosen as performance metric. For example, objective tests of the
understandability use automatic speech recognition (ASR) systems and
measure the amount of correctly detected words.

In any case, the participant shall be informed about the quality of
connection, the presence of high delays, the half-duplex style of
communication, and its (limited) righttospeak. For example this can
be achieved by a simulated talker echo.

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9.8. Discussion

The requirements of the usage scenarios are summarized in the
following table.

|     Sound Quality  |      Latency       | Complexity
Scenario   | low  | avg. | hifi | 10ms | 150ms| high | low  | high
-------------+------+------+------+------+------+------+------+-----
VoIP         |   X  |      |      |      |   X  |      |   X  |   X
AoIP         |      |   X  |   X  |      |   X  |      |      |   X
Conference   |      |   X  |      |      |   X  |      |      |   X
Convergence  |   X  |      |      |      |   X  |      |   X  |   X
Streaming    |      |   X  |   X  |      |      |   X  |      |   X
Performances |      |      |   X  |   X  |      |      |      |   X
Push-To-Talk |   X  |      |      |      |      |   X  |   X  |   X

Figure 6 Different requirements for different usage scenarios

10. Recommendations for Testing the IIAC

The IETF IIAC differs substantially from a classic narrow and
wideband codec. Thus, the previously applied codec testing
one must check carefully, which of the procedures are used without
changes, which procedures are used with minor changes and which
procedures are dropped or replaced.

In Section 1 we listed five groups of stakeholders, which have
different requirements and demands on how to test the quality of an
IIAC. In the following, we recommend testing procedures for those
stakeholders.

10.1. During Codec Development

The codec development is an innovative process. In general,
innovation and research in general benefits from openness and
discussion between experts. Thus, format restrictions on how to test
the codec might hinder the codec development because innovation may
also take place in testing procedures. Instead, many experts both in
codec development and codec usage shall be able to participate. If
this is the case, they contribute with their expertise, identify
weaknesses, and discuss potential codec enhancements. During
innovation, openness in participation and discussion is very
fruitful and leads to good results.

Based on the ongoing experience, codec developers know best on how
to tests their codecs. Typically, those tests include informal

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testing, semiformal testing, and expert interviews. They are
intended to find weaknesses in the codec, to identify artifacts or
distortions, and to achieve algorithmic progress.

10.2. Characterization Phase

The characterization phase is intended to study the features, the
quality tradeoff and the properties of a codec under
standardization. It is intended to be an objective measure of the
codec's quality to convince third parties of the quality properties
of the standardized codec. In order to achieve this aim, a formal
testing procedure has to be established.

In general, we recommend to base the procedure of the
characterization phase on procedures that are similar to those that
were used for the G.719 standardization (Section 7.2 and especially
[35]). In the following, we describe the suggested testing procedure
in the characterization phase.

10.2.1. Methodology

The testing of sound quality can be done using the MUSHRA tests
with eight samples and three anchors. One anchor is the known
reference, the second one is a hidden reference, and the third one
the hidden anchor. It is suggested to use a bandwidth filtered
signal with at low-pass filter at 3.5 kHz. However, because a will
range of qualities are to be tested ranging from Hifi down to toll
quality, it is beneficial to add a further low quality anchor such
as a 3.5 kHz bandwidth sample distorted by modulated noise (MNRU)
[25], for example with MNRU of a strength of Q=25 dB that
corresponds to a MOS value of 1.79 [4].

10.2.2. Material

Reference samples should be 48 kHz sampled, stereo channel material.
The nominal bandwidth of the reference samples shall be limited to
the range of 20 to 20000 Hz. Three different kinds of contents shall
be tested: speech, music and mixed content.

Speech samples shall include different languages including English
and tonal languages. The speech samples shall be recorded in a quiet
environment without background noise or reverberations. The speech
samples shall contain one meaningful sentence having a length of

Music samples shall contain a wide variety of music styles including
classical music, pop, jazz, and single instruments. The length of

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samples shall be of between 10 and 15 s. A smoothing of 100 ms both
at the beginning and at the end shall be conducted, if required.

jingles and other mixtures of speech, music and noises. The length
may be at about 5-6 s.

10.2.3. Listening Laboratory

Multiple independent laboratories shall conduct the listening tests.
They are responsible for generating or selecting reference samples
as well as for the pre and post screening of subjects. In the end,
the results of about 24 experienced listeners shall be published (in

The tests must be conducted in a quiet listening environment at
about NC25 (approximate 35 dBA). For example, an ISOBOOTH room can
be used.

It is recommended to use a high quality D/A, such as Benchmark DAC,
Metric Halo ULN-2, Apogee MiniDAC. High quality headphone amplifiers
and playback level calibration shall be used. Playback levels might
be measured via Etymotic in-ear microphones. Also, high quality

The IIAC is likely to be highly configurable. However, due to time
limits, only a few parameter sets can be tested subjectively. Thus,
we recommend to do subjective studies with

o different bit rates (from low to high, 5 tests)

o different frame rates (from low to high, 2 tests)

o different loss pattern (G.1050 profile A, B, and C at low rate
with speech content and at high rate with music content. The
influence of jitter, delay, and link failures shall be ignored.
In total, this would be 6 tests)

o different sample contents

o Speech, speech+reverberations, and speech+noise+reverberations
at low and medium rates (3 tests).

o The speech sample must be tested in different languages
(English, Chinese, ...) and with male/female voices (6 tests)

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o Mixed content and music shall be tested at medium and high

o A low complexity mode, DTX and the FEC mode shall be tested at
low rates because they are typically used on constraint devices
(3 tests)

o Abrupt changes in bit and frame rates (reduction by half,
exponential start, 2 tests)

o Smooth changes of bit and frame rates (incrementing or degreasing
the codec's gross rate by 1.5 kbyte every 100ms, 2 tests)

o Stall and continue operations (20, 200, and 1000 ms, 3 tests)

o Accelerated and slowed down playout (+- 10% for speech at low
rates)

o Reference codecs such as LAME MP3, G.719, and AMR each at two
coding rate (6 tests)

Already, these are 48 different tests that need to be conducted.

In addition, for intermediate values objective tests shall be run
using PEAQ (for music) and P.OLQA (for speech). The intermediate
results shall be mapped on the MUSHRA scale with a quadratic
regression because PEAQ and P.OLGA are using an ODG and MOS scale
respectively.

10.3. Application Developers

Application developers can take advantage of the results of the
qualification phase. They may use the results to develop a quality
model, which describes the expected quality of the codec at a given
parameter set (refer to [11] for an example).

In addition, they can test their system using the draft G.1050
simulation model, which is especially useful for optimizing rate
control, dejittering buffers and concealment algorithms. Different
systems may be tested with quality models, subjective listening
tests, conversational listening tests, or with objective measures
such as POLQA.

Also, field tests may be conducted to test the effect of a real
network on the VoIP application.

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10.4. Codec Implementers

To tests the conformance of a codec, codec implementers can use
objective tools like PEAQ or P.OLQA to see, whether the newly
implemented codec performs in a way that is similar to the
performance of the reference implementation. These tests shall be
done for many different parameter sets.

10.5. End Users

End user may be included in the qualification tests. The intentions
of these tests are two-fold. First, the awareness of the end-user
shall be increased. Second, querying users may be a cost effective
way of conducting listening-only tests.

However, before the rating results of end users can be considered
for further usage, one need to compare between formal and web-based
testing results to see, to what extent they differ from each other.

11. Security Considerations

The results of the quality tests shall be convincing. Thus, special
care has to be taken to make the tests precise, accurate, repeatable
and trustworthy.

Some testing houses may have a conflict of interest between accurate
quality ratings and promotion of own codecs. Thus, a high degree of
openness shall be enforced that requires all of the testing material
and results to be published. This way, others may verify the results
of testing houses. In addition, some stimuli shall be tested by all
the testing houses to compare their quality of rating.

Moreover, hidden anchors may help to identify subjects, which rate
the quality of samples less precisely.

12. IANA Considerations

This document has no actions for IANA.

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13. References

13.1. Normative References

13.2. Informative References

[1]  R. Birke, M. Mellia, M. Petracca, D. Rossi, "Understanding
VoIP from Backbone Measurements", IEEE INFOCOM 2007, 26th IEEE
International Conference on Computer Communications, pp.2027-
2035, May 2007.

[2]  C. Boutremans, J.-Y. Le Boudec, "Adaptive joint playout buffer
and FEC adjustment for Internet telephony," IEEE Societies
INFOCOM 2003. Twenty-Second Annual Joint Conference of the
IEEE Computer and Communications., vol.1, pp. 652- 662 vol.1,
30 March-3 April 2003.

[3]  Broadcom, "BCM1103: GIGABIT IP PHONE CHIP", Jan. 2005,
http://www.datasheetcatalog.org/datasheet2/3/07ozspx224dsarq6z
u13i2ofyqyy.pdf

[4]  N. Cote, V. Koehl, V. Gautier-Turbin, A. Raake, S. Moeller,
"Reference Units for the Comparison of Speech Quality Test
Results", Audio Engineering Society Convention 126, May 2009.

[5]  Ericsson, "Analysis of PEAQ's applicability in predicting the
quality difference between alternative implementations of the
G.722.1FB coding algorithm", ITU-T SG12, Received on 2008-05-
09, Related to question(s) : Q9/12, Meeting 2008-05-22.

[6]  ETSI TC-TM, "ETR 250: Transmission and Multiplexing (TM);
Speech communication quality from mouth to ear for 3,1 kHz
handset telephony across networks", ETSI Technical Report,
July 1996.

[7]  S. Floyd, E. Kohler, "Profile for Datagram Congestion Control
Protocol (DCCP) Congestion ID 4: TCP-Friendly Rate Control for
Small Packets (TFRC-SP)", RFC 5622, August 2009.

[8]  S. Floyd, E. Kohler, "TCP Friendly Rate Control (TFRC): The
Small-Packet (SP) Variant", RFC 4828, April 2007.

[9]  J. Gruber, G. Williams, Transmission Performance of Evolving
Telecommunications Networks, Artech House, 1992.

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[10] M. Gurevich, C. Chafe, G. Leslie, S. Tyan, "Simulation of
Networked Ensemble Performance with Varying Time Delays:
Characterization of Ensemble Accuracy", Proceedings of the
2004 International Computer Music Conference, Miami, USA,
2004.

[11] C. Hoene, H. Karl, A. Wolisz, "A perceptual quality model
intended adaptive VoIP applications", International Journal of
Communication Systems, Wiley, August 2005.

[12] J. Holub, J.G. Beerends, R. Smid, "A dependence between
average call duration and voice transmission quality:
measurement and applications," Wireless Telecommunications
Symposium, 2004, pp. 75- 81, May 2004.

[13] ITU, "Incoming LS: Proposed G.1050/TIA-921B IP Network Model
Simulation", ITU-T SG 12, Temporary Document 268-GEN, May 12,
2010.

[14] ITU, "ITU-R BS.1116-1: Methods for the subjective assessment
of small impairments in audio systems including multichannel
sound systems", Recommendation, October 1997.

[15] ITU, "ITU-R BS.1387: Method for objective measurements of
perceived audio quality", Recommendation, November 2001.

[16] ITU, "ITU-R BS.1534-1: Method for the subjective assessment of
intermediate quality levels of coding systems",
Recommendation, January 2003.

[17] ITU, "ITU-T G.107: The E-model: a computational model for use
in transmission planning", Recommendation, April 2009.

[18] ITU, "ITU-T G.114: One-way transmission time", Recommendation,
May 2003.

[19] ITU, "ITU-T G.191: Software tools for speech and audio coding
standardization", Recommendation, March 2010.

[20] ITU, "ITU-T G.1050: Network model for evaluating multimedia
transmission performance over Internet Protocol",
Recommendation, November 2007.

[21] ITU, "ITU-T G.RQAM, "Reference guide to QoE assessment
methodologies", standard draft TD 310rev1, May 2010.

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[22] ITU, "ITU-T P.10/G.100: Vocabulary and effects of transmission
parameters on customer opinion of transmission quality",
Recommendation, July 2006.

[23] ITU, "ITU-T P.800: Methods for objective and subjective
assessment of quality", Recommendation, August 1996.

[24] ITU, "ITU-T P.805: Subjective evaluation of conversational
quality", Recommendation, April 2007.

[25] ITU, "ITU-T P.810: Modulated noise reference unit (MNRU)",
Recommendation, February 1996.

[26] ITU, "ITU-T P.830: Subjective performance assessment of
telephone-band and wideband digital codecs", Recommendation,
February 1996.

[27] ITU, "ITU-T P.862: Perceptual evaluation of speech quality
(PESQ): An objective method for end-to-end speech quality
assessment of narrow-band telephone networks and speech
codecs", Recommendation, February 2001.

[28] ITU, "ITU-T P.862.1: Mapping function for transforming P.862
raw result scores to MOS-LQO", Recommendation, November 2003.

[29] ITU, "ITU-T P.862.2: Wideband extension to Recommendation
P.862 for the assessment of wideband telephone networks and
speech codecs", Recommendation, November 2007.

[30] ITU, "ITU-T P.862.3: Application guide for objective quality
measurement based on Recommendations P.862, P.862.1 and
P.862.2", Recommendation, November 2007.

[31] ITU, "ITU-T P.880: Continuous evaluation of time-varying
speech quality", Recommendation, May 2004.

[32] H. Jiang, C. Dovrolis, "Why is the internet Traffic Bursty in
Short Time Scales?" Sigmetrics'05, Banff, Alberta, Canada,
June 2005.

[33] C. Lamblin, R. Even, "Processing Test Plan for the ITU-T
G.722.1 fullband extension optimization/characterization
phase", ITU-T Study Group 16, Temporary Document TD 322 (WP
3/16), 22 April - 2 May 2008.

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[34] C. Lamblin, R. Even, "G.722.1 fullband extension
characterization phase test results: objective (ITU-R BS.1387-
1) and subjective (ITU-R BS.1116) scores", ITU-T Study Group
16, Temporary Document TD 341 R1 (WP 3/16), 22 April - 2 May
2008.

[35] C. Lamblin, R. Even, "G.722.1 fullband extension
optimization/characterization Quality Assessment Test Plan",
ITU-T Study Group 16, Temporary Document TD 323 (WP 3/16), 22
April - 2 May 2008.

[36] J. Lee, J. Kim, C. Jang, S. Kim, B. Egger, K. Kim, S Han,
"FaCSim: A Fast and Cycle-Accurate Architecture Simulator for
Embedded Systems", in Proceedings of the International
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14. Acknowledgments

This document is based on many discussions with experts in the field
of codec design, quality of experience and quality management. My
special thanks go to Michael Knappe, Sebastian Moeller, Raymond
Chen, Jack Douglass, Paul Coverdale, Jean-Marc Valin, Koen Vos,
Bilke Ullrich, and all active participants of the Codec WG mailing
list. Also, I like to express my appreciation to the members of the
ITU-T study groups 12 and 16, with whom I had many fruitful
discussions.

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Christian Hoene
Universitaet Tuebingen
WSI-ICS
Sand 13
72076 Tuebingen
Germany

Phone: +49 7071 2970532
Email: hoene@uni-tuebingen.de

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