WO2005083921A1 - Procede pour prevoir la qualite de perception de signaux audio - Google Patents
Procede pour prevoir la qualite de perception de signaux audio Download PDFInfo
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- WO2005083921A1 WO2005083921A1 PCT/FI2004/050020 FI2004050020W WO2005083921A1 WO 2005083921 A1 WO2005083921 A1 WO 2005083921A1 FI 2004050020 W FI2004050020 W FI 2004050020W WO 2005083921 A1 WO2005083921 A1 WO 2005083921A1
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- signal
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- distortion
- linear
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/20—Arrangements for detecting or preventing errors in the information received using signal quality detector
Definitions
- This invention relates generally to a signal processing and particularly to such processing, where the signal is being subjected to linear or non-linear distortion.
- Audio signals are often distorted by transducers, such as e.g. loudspeakers and microphones, transducer amplifiers and equalizers, audio and speech coders as well as many transmission channels. These transducers, loudspeakers, microphones etc. can be found also in mobile communication devices. Due to the distortion the received or reproduced signal is not identical to the original and a decreasing of tone quality is considerable. The distortion can be categorized into linear and non-linear distortion.
- Linear distortion involves changes in relative amplitudes and phases of frequency components present in a complex signal. Such changes are typically perceived as changes in timbre or in tone quality (coloration).
- the perceptual effects of linear distortion are discussed in several studies of related art, e.g. "Toole, F.E.: Loudspeaker measurements and their relationship to listener preferences, Part 1 (J. Audio Eng. Soc. 34, pages 227 - 235) and Part 2 (J. Audio Eng. Soc. 34, pages 323 - 348), 1986” and "Gabrielsson, A. & al: Perceived sound quality of reproductions with different frequency responses and sound levels (J. Acoust. Soc. Am. 88, pages 1359 - 1366), 1990". These studies have not given proposals for calculating the perceived quality of sounds that have been affected by said distortion.
- Non-linear distortion introduces frequency components that were not present in the input signal. Effects of nonlinear distortion may be described as “harshness” or “roughness” or in terms of the perception of sounds that were not present in the original signal such as “crackles” or “clicks”.
- the non-linear distortion of the signal may be dependent, e.g., on the level and/or the phase of the signal. In a speaker the distortion can depend, e.g. on displacement of a coil.
- form of the non-linear distortion may be symmetric or asymmetric, and the distortion can appear as harmonic or inharmonic.
- the level of non-linearity may vary from weak to strong or even to chaotic.
- the audio processing methods of related art lack suitable methods for predicting the perceived quality of signals that have been subjected to linear and/or non-linear distortion. Especially when the distortion is of that type, which is produced by electro- acoustic transducers such as microphones and loudspeakers. For assessing the perceived quality of sounds transduced by microphones and loudspeakers a representative panel of human listeners should be used to obtain subjective judgments. It is obvious that this kind of arrangement is expensive and time-consuming.
- the aim of the current invention is to provide an objective method for predicting the perceived quality (naturalness) of audio signals that have been affected by linear or non-linear distortion or by combination of those two.
- the invention suggests one method, which can be applied to said distortions by means of three models.
- Another aim of the current invention is to provide a method that can be utilized in broadcasting, telecommunications, sound reproduction, sound recording and sound coding. Naturally, the invention is also applicable in other applications.
- Yet another aim of the current invention is to provide models for the linear and the non-linear and the combined distortion, which can be used in product audio quality assurance process, where said models can be used to evaluate the acoustic signal that is reproduced by e.g. an earpiece or a loudspeaker.
- the linear model can be used to predict the quality with respect to spectral distortion and the non-linear model with respect to signal clipping.
- the invention is characterized in that a type of a distortion is determined and depending on whether linear distortion, non-linear distortion, or both are detected, a model for quality prediction is selected and the quality of the distorted signal is determined.
- the method according to the invention can give a direct estimate of the quality as perceived by human listeners, enabling e.g. a perceptually-valid comparison of different solutions for a product.
- the method according to the invention is objective and the predictions appear to correlate highly with the mean ratings of human listeners' panels. Due to the invention, the evaluation of transducers and transmission channels can be implemented without a need to run expensive listening tests with large panels.
- Figure 1 is a block model of an embodiment of a linear model according to the invention
- Figure 2 is a block model of an embodiment of a non-linear model according to the invention.
- Figure 3 is a block model of an embodiment of a combined model according to the invention.
- the method for predicting the perceived quality of audio signals according to the invention is divided into three models according to the type of distortion.
- the models can be applied e.g. to speech or music signals.
- Signals can be either acoustic or electrical (analog or digital).
- a frequency response of a device in question is taken as an input to evaluate device's perceptual effect on audio signal.
- the model can be used to study any spectral distortion, despite whether the distortion is generated e.g. through a transducer or in analog or digital filtering system of electric signals.
- a time-domain speech or music signal can be taken as an input to evaluate signal's perceptual quality.
- the signal may be generated through e.g. a transducer or processed by any analog or digital signal processing system in electric domain.
- the model is relatively independent of linear distortion, so the input signals may also include linear distortion. However this may not affect quality predictions for non-linear distortion.
- both the frequency response and the waveform of the signal under study are taken as inputs.
- the model is able to separate effects of linear and non-linear distortion on perceptual quality as well as to predict the combined effect on quality.
- the linear model describes how the method according to the invention is used for predicting the perceptual quality of signals that have been affected by linear distortion.
- a quantity being inversely related to the subjective naturalness of a signal subjected to a specific spectral distortion is generated. This model is described with reference to figure 1.
- a complex test signal PN e.g. speech-shaped noise, pink noise, white noise, real speech just to mention few potentials
- the input level is adjusted ADJ so that the loudness level N of the output corresponds to a predetermined value, e.g. 86.4 phons.
- Loudness level of time-invariant signals can be calculated e.g. by: Zwicker's model or Moore's model. These models are, however, often also applied to time-varying signals by computing the loudness for short signal frames. For time-varying signals also Glasberg and Moore's temporal loudness model can be used. Other models are also known, which can be used, so the invention is not limited only to one particular method.
- An excitation pattern is calculated EP next according to some known method.
- the calculation can follow e.g. the Moore model with use of a sharpening parameter SP.
- the sharpness of filters used to calculate the excitation pattern can be controlled by a parameter P, whose value at each centre frequency FC determines both bandwidth and slope of the filter; the higher the value of the parameter P the shaper the filter is.
- the filters are sharpened by multiplying the parameter value P at each centre frequency FC by the sharpening parameter SP.
- the excitation pattern can be calculated as a function of ERB N number "i" at intervals of 0.5 ERB N , for the original undistorted signal and the spectrally distorted signal.
- ERB N signifies the mean equivalent rectangular bandwidth of the auditory filter for young normally hearing listeners at moderate sound levels.
- the calculated excitation level for any value of "i" is compared CMP to a noise floor value F.
- the excitation level falls below the value F the excitation level is set equal to the noise floor value F.
- second-order difference DIFF2 is determined for each value of "i" between the excitation level EO for the original signal and the excitation level ED for the spectrally distorted signal;
- w s 0.5.
- the values of W(i) are set to 0 for "i" ⁇ 4 and for "i" > 36.
- the standard deviation SD of the weighted first-order differences WD1 is determined across all "i". Also the standard deviation SD of the weighted second-order WD2 differences is determined across all "i”. Standard deviation can be determined by subtracting the overall averages avg(WD1 (i)) and avg(WD2(i)) from WD1(i) and WD2(i) for each value correspondingly. Those differences are then multiplied by themselves. The resulting squared values are summed after which those results are divided by (n-1) (n is number of values). The standard deviation is the square root of those ratios.
- D wSD ⁇ EO(i) - ED(i) ⁇ + (1-w)SD ⁇ EO(i+1) - ED(i+1) - EO(i) + ED(i) ⁇
- the final calculated quantity is referred by the overall weighted excitation-pattern difference D.
- Subjective naturalness is inversely related to excitation-pattern difference D and predictable from excitation-pattern difference D.
- the first step is to apply a linear transform to each subjective rating score S UN so that the range of transformed scores Sj, is from 0 to 1 :
- MIN is the smallest obtained value of subjective judgement S and MAX is the largest.
- Frequency regions are characterized in terms of (modelled) auditory filters.
- the extent to which the output in one filter (frequency region) is caused by the input in that filter, can be measured by the correlation of the output of a simulated auditory filter in response to the original and distorted signals; the higher the correlation of the filter responses to the original and distorted signals, the lower is the distortion, and the higher is the perceptual quality.
- This model comprises following steps:
- the input signal is e.g. speech signal (for prediction of speech data) or music signal (for prediction of music data).
- the model requires the waveform of the original input signal and the waveform of the signal after passing the non-linear system under test.
- the original Ol and distorted Dl signals are time aligned TA.
- the original Ol and distorted Dl signals are filtered to mimic the effects of transmission through the outer and middle ear. This can be done by using a finite impulse response (FIR) filter with 4097 coefficients.
- Analog signals are at first converted into digital format AD and saved into memory MEM. Signal and corresponding coefficient CO are fetched from the memory and applied to the multiplier MA. The resulting products are summed for producing the digital filtered signal, which is then converted DA into analog format.
- the filtered signals Ol, Dl are fed (separately) to an array of 40 gammatone filters each 1 - ERBN wide FB.
- the cross- correlation CC between the response to the undistorted signal and the response to the distorted signal is determined. This is done in 30 ms non-overlapping frames. For each frame and each filter, the maximum value MAX of the cross correlation is determined: this allows for any (small) frequency-dependent time delay in the non-linear system. For each 30 ms frame "i”, the power at the output of each filter "j" is calculated and converted to a decibel measure Level(j) DB. The value of Level(j) is used to determine a weight that is applied to the short- term correlation for frame "i" and filter "j". The weights are scaled separately for each frame so that the sum of the weights is unity.
- Empirical data show that the function relating subjective scores S NO NUN to Rnonlin is sigmoidal in shape. This function is described by four parameters (lower asymptote, upper asymptote, slope, and Rnonlin value giving a medium rating).
- the function is used to predict the score S N ONUN- for a given type of distortion from the Rnonlin value for that distortion.
- This model introduces the method for predicting the perceptual quality of signals subjected to combined linear and non-linear distortion This model is described with reference to figure 3.
- the linear model gives a predicted score SUN (based on a test signal).
- the non-linear model gives a predicted score SNONLIN (using speech or music as input, as appropriate).
- ⁇ is a parameter of the model that characterizes the relative importance of the linear and non-linear parts of the distortion.
- ⁇ is a parameter of the model that characterizes the relative importance of the linear and non-linear parts of the distortion.
- the most accurate predictions are obtained with ⁇ set to a small value, such as 0.05, indicating that linear distortion has smaller perceptual effects than non-linear distortion.
- the linear model is non-intrusive, which means that the model does not require any reference signal when predicting spectral quality.
- the model could be used in e.g. mobile terminal for controlling adaptive equalization of an earpiece signal, when the acoustic response of the earpiece is known.
- the linear model could be used to adapt the equalizer within certain constraints to reproduce an optimal acoustic response.
- the non-linear model is intrusive and requires a reference signal. In this way, it could be used for the quality prediction of signals that are stored into terminal's memory.
- the model could be applied to measuring the quality of audio samples stored into terminals (e.g., down-loaded music, MIDI, etc.)
- an adaptive equalizer or dynamic range control is used to optimise the level versus quality of a music signal.
- the user of a mobile terminal might wish to increase the loudness of the music sample and the non-linear model would be used to decide what increase can still be allowed without causing perceptual degradation of audio quality.
- the model for non-linear distortion can also be used for controlling substantially any speech-processing algorithm, if the input signal is taken as a reference signal. Even if the signal has already been corrupted in previous processing blocks.
- the model could also produce accurate predictions in cases where the reference is not representing non-processed quality.
- the method according to the invention can be implemented by a computer program that comprises computer readable instructions for receiving a specification of the frequency response and time waveforms of test signals.
- the computer program can be written in any relevant programming language, e.g. in MATLAB or C / C++ and be saved in a memory of any suitable computer program product.
- the method according to the invention can be also implemented by a stand-alone system arranged in a digital-signal-processing chip.
- Frequency response is acquired from the device where the system or the program is arranged as well as the time waveforms are at the input and output of the device. According to one implementation the frequency response is determined from the two time waveforms.
- the system and/or computer program can be arranged into devices such as audio quality testing devices but also mobile terminals to control audio and speech processing algorithms due to its relative low computational complexity. In that situation it could be used for tuning transducer equalizers, controlling signal compression and gain control.
- devices such as audio quality testing devices but also mobile terminals to control audio and speech processing algorithms due to its relative low computational complexity. In that situation it could be used for tuning transducer equalizers, controlling signal compression and gain control.
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- Engineering & Computer Science (AREA)
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- Computer Networks & Wireless Communication (AREA)
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- Compression, Expansion, Code Conversion, And Decoders (AREA)
Abstract
La présente invention concerne un procédé de traitement des signaux selon lequel le signal est soumis à une distorsion et une qualité subjective du signal est déterminée. Un type de distorsion est déterminé et, en fonction de si une distorsion linéaire, une distorsion non linéaire ou les deux sont détectées, un modèle de prévision de qualité est sélectionné et la qualité du signal soumis à la distorsion est déterminée. La qualité subjective du signal soumis à cette distorsion est déterminée. La présente invention concerne également un système et un produit programme informatique permettant de mettre en oeuvre les modèles de prévision.
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PCT/FI2004/050020 WO2005083921A1 (fr) | 2004-02-27 | 2004-02-27 | Procede pour prevoir la qualite de perception de signaux audio |
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Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2022225413A1 (fr) | 2021-04-23 | 2022-10-27 | Harman International Industries, Incorporated | Procédé et système de détermination d'une qualité sonore d'un système audio |
WO2023018349A1 (fr) | 2021-08-13 | 2023-02-16 | Harman International Industries, Incorporated | Procédé de détermination d'une réponse en fréquence d'un système audio |
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EP0946015A1 (fr) * | 1998-03-27 | 1999-09-29 | Ascom Infrasys AG | Procédé et dispositif d'estimation de la qualité de transmission |
EP1089429A2 (fr) * | 1999-09-29 | 2001-04-04 | Toshiba Corporation | Circuit de commande automatique de gain et récepteur comportant un tel circuit |
US20040025669A1 (en) * | 2002-08-09 | 2004-02-12 | Sony Corporation/Sony Music Entertainment | Audio quality based culling in a peer-to peer distribution model |
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2004
- 2004-02-27 WO PCT/FI2004/050020 patent/WO2005083921A1/fr active Application Filing
Patent Citations (4)
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US5886988A (en) * | 1996-10-23 | 1999-03-23 | Arraycomm, Inc. | Channel assignment and call admission control for spatial division multiple access communication systems |
EP0946015A1 (fr) * | 1998-03-27 | 1999-09-29 | Ascom Infrasys AG | Procédé et dispositif d'estimation de la qualité de transmission |
EP1089429A2 (fr) * | 1999-09-29 | 2001-04-04 | Toshiba Corporation | Circuit de commande automatique de gain et récepteur comportant un tel circuit |
US20040025669A1 (en) * | 2002-08-09 | 2004-02-12 | Sony Corporation/Sony Music Entertainment | Audio quality based culling in a peer-to peer distribution model |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2022225413A1 (fr) | 2021-04-23 | 2022-10-27 | Harman International Industries, Incorporated | Procédé et système de détermination d'une qualité sonore d'un système audio |
DE112021007572T5 (de) | 2021-04-23 | 2024-02-15 | Harman International Industries, Incorporated | Verfahren und System zum Bestimmen einer Tonqualität eines Audiosystems |
WO2023018349A1 (fr) | 2021-08-13 | 2023-02-16 | Harman International Industries, Incorporated | Procédé de détermination d'une réponse en fréquence d'un système audio |
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