Evaluating the Generalization of the Hearing Aid Speech Quality Index (HASQI)

Many developers of audio signal processing strategies rely on objective measures of quality for initial evaluations of algorithms. As such, objective measures should be robust, and they should be able to predict quality accurately regardless of the dataset or testing conditions. Kates and Arehart have developed the Hearing Aid Speech Quality Index (HASQI) to predict the effects of noise, nonlinear distortion, and linear filtering on speech quality for both normal-hearing and hearing-impaired listeners, and they report very high performance with their training and testing datasets [Kates, J. and Arehart, K., Audio Eng. Soc., 58(5), 363-381 (2010)]. In order to investigate the generalizability of HASQI, we test its ability to predict normal-hearing listeners' subjective quality ratings of a dataset on which it was not trained. This dataset is designed specifically to contain a wide range of distortions introduced by real-world noises which have been processed by some of the most common noise suppression algorithms in hearing aids. We show that HASQI achieves prediction performance comparable to the Perceptual Evaluation of Speech Quality (PESQ), the standard for objective measures of quality, as well as some of the other measures in the literature. Furthermore, we identify areas of weakness and show that training can improve quantitative prediction.

[1]  Thomas Sporer,et al.  PEAQ - The ITU Standard for Objective Measurement of Perceived Audio Quality , 2000 .

[2]  Yi Hu,et al.  Evaluation of Objective Quality Measures for Speech Enhancement , 2008, IEEE Transactions on Audio, Speech, and Language Processing.

[3]  Marcus Holmberg,et al.  Validation of Objective Sound Quality Models for Hearing Aids , 2010 .

[4]  Birger Kollmeier,et al.  Using a quantitative psychoacoustical signal representation for objective speech quality measurement , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[5]  IEEE Recommended Practice for Speech Quality Measurements , 1969, IEEE Transactions on Audio and Electroacoustics.

[6]  Antony William Rix,et al.  Perceptual evaluation of speech quality (PESQ): The new ITU standard for end-to-end speech quality a , 2002 .

[7]  T. Dau,et al.  A quantitative model of the "effective" signal processing in the auditory system. II. Simulations and measurements. , 1996, The Journal of the Acoustical Society of America.

[8]  Muhammad S A Zilany,et al.  Representation of the vowel /epsilon/ in normal and impaired auditory nerve fibers: model predictions of responses in cats. , 2007, The Journal of the Acoustical Society of America.

[9]  J. Kates.  A central spectrum model for the perception of coloration in filtered Gaussian noise. , 1985, The Journal of the Acoustical Society of America.

[10]  T Dau,et al.  A quantitative model of the "effective" signal processing in the auditory system. I. Model structure. , 1996, The Journal of the Acoustical Society of America.

[11]  John G. Beerends,et al.  A Perceptual Audio Quality Measure Based on a Psychoacoustic Sound Representation , 1992 .

[12]  David V. Anderson,et al.  Robustness of the Hearing Aid Speech Quality Index (HASQI) , 2011, 2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA).

[13]  Ian C. Bruce,et al.  Representation of the vowel /ε/ in normal and impaired auditory nerve fibers: Model predictions of responses in cats , 2007 .

[14]  Andries P. Hekstra,et al.  Perceptual evaluation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[15]  Brian C J Moore,et al.  Perception of nonlinear distortion by hearing-impaired people , 2008, International journal of audiology.

[16]  J M Kates,et al.  Quality ratings for frequency-shaped peak-clipped speech: results for listeners with hearing loss. , 1996, Journal of Speech and Hearing Research.

[17]  Vijay Parsa,et al.  Hearing Aid Distortion Measurement Using the Auditory Distance Parameter , 2001 .

[18]  Matti Karjalainen,et al.  A new auditory model for the evaluation of sound quality of audio systems , 1985, ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[19]  L. Auger.  The Journal of the Acoustical Society of America , 1949 .

[20]  J M Kates,et al.  Quality ratings for frequency-shaped peak-clipped speech. , 1994, The Journal of the Acoustical Society of America.

[21]  Brian C. J. Moore,et al.  Predicting the Perceived Quality of Nonlinearly Distorted Music and Speech Signals , 2004 .

[22]  A.W. Rix,et al.  The perceptual analysis measurement system for robust end-to-end speech quality assessment , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[23]  Thomas Baer,et al.  A model for the prediction of thresholds, loudness, and partial loudness , 1997 .

[24]  Andrew Sekey,et al.  An Objective Measure for Predicting Subjective Quality of Speech Coders , 1992, IEEE J. Sel. Areas Commun..

[25]  A. Berger.  FUNDAMENTALS OF BIOSTATISTICS , 1969 .

[26]  James M Kates,et al.  Effects of noise and distortion on speech quality judgments in normal-hearing and hearing-impaired listeners. , 2007, The Journal of the Acoustical Society of America.

[27]  Birger Kollmeier,et al.  Objective Modeling of Speech Quality with a Psychoacoustically Validated Auditory Model , 2000 .

[28]  J. Cavanaugh.  Biostatistics , 2005, Definitions.

[29]  Edward Jones,et al.  Audio quality assessment techniques - A review, and recent developments , 2009, Signal Process..

[30]  Carolyn Yarnall,et al.  Model structure , 2021, Integrated Simulation Framework II – Model for Palestinian Economic Policy.

[31]  John H. L. Hansen,et al.  An effective quality evaluation protocol for speech enhancement algorithms , 1998, ICSLP.

[32]  James M. Kates,et al.  The Hearing-Aid Speech Quality Index (HASQI) , 2010 .

[33]  Martin Hansen,et al.  Assessment and prediction of speech transmission quality with an auditory processing model , 1998 .

[34]  M. Hansen,et al.  Continuous assessment of time-varying speech quality. , 1999, The Journal of the Acoustical Society of America.

[35]  Ronald E. Crochiere,et al.  A study of complexity and quality of speech waveform coders , 1978, ICASSP.

[36]  Vijay Parsa,et al.  Loudness pattern-based speech quality evaluation using bayesian modeling and Markov chain Monte Carlo methods. , 2007, The Journal of the Acoustical Society of America.

[37]  Schuyler Quackenbush,et al.  Objective measures of speech quality , 1995 .

[38]  Kamal Ahmed,et al.  Degradation decomposition of the perceived quality of speech signals on the basis of a perceptual modeling approach , 2007 .

[39]  Koen Eneman,et al.  Speech Quality Measurement for the Hearing Impaired on the Basis of PESQ , 2008 .

[40]  Brian C. J. Moore,et al.  Development and Validation of a Method for Predicting the Perceived Naturalness of Sounds Subjected to Spectral Distortion , 2004 .

[41]  Birger Kollmeier,et al.  PEMO-Q—A New Method for Objective Audio Quality Assessment Using a Model of Auditory Perception , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[42]  Yi Hu,et al.  Subjective comparison and evaluation of speech enhancement algorithms , 2007, Speech Commun..