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Perceptual Objective Listening Quality Analysis

Perceptual Objective Listening Quality Analysis is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Perceptual Objective Listening Quality Analysis rather than just read about it. In short: Perceptual Objective Listening Quality Analysis (POLQA) was the working title of an ITU-T standard that covers a model to predict speech quality by means of analyzing digital speech signals. The model was standardized as Recommendation ITU-T P.863 (Perceptual objective listening quality assessment) in 2011.

Key takeaways

  • Perceptual Objective Listening Quality Analysis belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Perceptual Objective Listening Quality Analysis to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Perceptual Objective Listening Quality Analysis from memory before moving on to harder problems.

Reference excerpt

Perceptual Objective Listening Quality Analysis (POLQA) was the working title of an ITU-T standard that covers a model to predict speech quality by means of analyzing digital speech signals. The model was standardized as Recommendation ITU-T P.863 (Perceptual objective listening quality assessment) in 2011. The second edition of the standard appeared in 2014, and the third, currently in-force edition was adopted in 2018 under the title Perceptual objective listening quality prediction.

Measurement scope POLQA covers a model to predict speech quality, by means of digital speech signal analysis. The predictions of those objective measures should come as close as possible to subjective quality scores as obtained in subjective listening tests. Usually, a Mean Opinion Score (MOS) is predicted. POLQA uses real speech as a test stimulus for assessing telephony networks.

Technology capabilities POLQA is the successor of PESQ (Recommendation ITU-T P.862). POLQA avoids weaknesses of the current P.862 model and is extended towards handling of higher bandwidth audio signals. Further improvements target the handling of time-called signals and signals with many delay variations. Similarly to P.862, POLQA supports measurements in the common telephony band (300–3400 Hz), but in addition it has a second operational mode for assessing HD-Voice in wideband and super-wideband speech signals (50–14000 Hz). POLQA also targets the assessment of speech signals recorded acoustically by an artificial head with mouth and ear simulators.

Development history The POLQA activities started in ITU-T in early 2006 under the working title P.OLQA. In mid-2009, a competition was started to evaluate several candidate models. In May 2010, ITU-T selected candidate models from three companies (OPTICOM, SwissQual / Rohde & Schwarz and TNO (Netherlands Organisation for Applied Scientific Research)). The three companies merged their approaches to one single model, which was adopted as Recommendation ITU-T P.863.

Genealogy of related standards ITU-T’s family of full reference objective voice quality measurements started in 1997 with Recommendation ITU-T P.861 (PSQM), which was superseded by ITU-T P.862 (PESQ) in 2001. P.862 was later complemented with Recommendations ITU-T P.862.1 (mapping of PESQ scores to a MOS scale), ITU-T P.862.2 (wideband measurements) and ITU-T P.862.3 (application guide). The first edition of ITU-T P.863 (POLQA) entered into force in 2011. An Application guide for Recommendation ITU-T P.863 was approved in 2019 and published as ITU-T P.863.1. In addition to the above listed full reference methods, the list of ITU-T’s objective voice quality measurement standards also includes ITU-T P.563 (no-reference algorithm).

Testing typology POLQA, similar to P.862 PESQ, is a Full Reference (FR) algorithm that rates a degraded or processed speech signal in relation to the original signal. It compares each sample of the reference signal (talker side) to each corresponding sample of the degraded signal (listener side). Perceptual differences between both signals are scored as differences. The perceptual psycho-acoustic model is based on similar models of human perception as MP3 or AAC. Basically, the signals are analysed in the frequency domain (in critical bands) after applying masking functions. Unmasked differences between the two signal representations will be counted as distortions. Finally, the accumulated distortions in the speech file are mapped into a 1 to 5 quality scale as usual for MOS tests. FR measurements deliver the highest accuracy and repeatability but can only be applied for dedicated tests in live networks (e.g. drive test tools for mobile network benchmarks). POLQA is a full-reference algorithm and analyzes the speech signal sample-by-sample after a temporal alignment of corresponding excerpts of reference and test signal. POLQA can be applied to provide an end-to-end (E2E) quality assessment for a network, or characterize individual network components. POLQA results principally model mean opinion scores (MOS) that cover a scale from 1 (bad) to 5 (excellent).

Description of the POLQA algorithm The inputs to the algorithm are two waveforms represented by two data vectors containing 16 bit PCM samples. The first vector contains the samples of the (undistorted) reference signal, whereas the second vector contains the samples of the degraded signal. The POLQA algorithm consists of a temporal alignment block, a sample rate estimator of a sample rate converter, which is used to compensate for differences in the sample rate of the input signals, and the actual core model, which performs the MOS calculation. In a first step, the delay between the two input signals is determined and the sample rate of the two signals relative to each other is estimated. The sample rate estimation is based on the delay information calculated by the temporal alignment. If the sample rate differs by more than approximately 1%, the signal with the higher sample rate is down sampled. After each step, the results are stored together with an average delay reliability indicator, which is a measure for the quality of the delay estimation. The result from the re-sampling step, which yielded the highest overall reliability, is finally chosen. Once the correct delay is determined and the sample rate differences have been compensated, the signals and the delay information are passed on to the core model, which calculates the perceptibility as well as the annoyance of the distortions and maps them to a MOS scale. A much more detailed and comprehensive description of the algorithm can be found in. The next few sections are only intended to give an overview on the basics of POLQA’s internal structure.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Perceptual Objective Listening Quality Analysis

Start with the simplest possible case. Write down what Perceptual Objective Listening Quality Analysis claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Perceptual Objective Listening Quality Analysis before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Perceptual Objective Listening Quality Analysis ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Perceptual Objective Listening Quality Analysis

In research
Perceptual Objective Listening Quality Analysis appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Perceptual Objective Listening Quality Analysis in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Perceptual Objective Listening Quality Analysis is common in secondary-school and first-year university syllabi. It links to neighbouring topics ITU-T P Series Recommendations, ITU-T recommendations, International standards, so understanding it makes those chapters shorter.
In everyday life
Look for Perceptual Objective Listening Quality Analysis outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Perceptual Objective Listening Quality Analysis in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Perceptual Objective Listening Quality Analysis means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Perceptual Objective Listening Quality Analysis out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Perceptual Objective Listening Quality Analysis in simple terms?

Perceptual Objective Listening Quality Analysis (POLQA) was the working title of an ITU-T standard that covers a model to predict speech quality by means of analyzing digital speech signals. The model was standardized as Recommendation ITU-T P.863 (Perceptual objective listening quality assessment)…

Why does Perceptual Objective Listening Quality Analysis matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Perceptual Objective Listening Quality Analysis?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Perceptual Objective Listening Quality Analysis.

Tags

  • ITU-T P Series Recommendations
  • ITU-T recommendations
  • International standards
  • Telecommunications

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