Audio scene analysis as a control system for hearing aids

It is well known that simple amplification cannot help many hearing-impaired listeners. As a consequence of this, numerous signal enhancement algorithms have been proposed for digital hearing aids. Many of these algorithms are only effective in certain environments. The ability to quickly and correctly detect elements of the auditory scene can permit the selection/parameterization of enhancement algorithms from a library of available routines. In this work, the authors examine the real time parameterization of a frequency-domain compression algorithm which preserves formant ratios and thus enhances speech understanding for some individuals with severe sensorineural hearing loss in the 2-3 kHz range. The optimal compression ratio is dependent upon qualities of the acoustical signal. We briefly review the frequency-compression technology and describe a Gaussian mixture model classifier which can dynamically set the frequency compression ratio according to broad acoustic categories which we call cohorts. We discuss the results of a prototype simulator which has been implemented on a general purpose computer.

[1]  Arne Leijon,et al.  An efficient robust sound classification algorithm for hearing aids. , 2004, The Journal of the Acoustical Society of America.

[2]  Alex Acero,et al.  Spoken Language Processing , 2001 .

[3]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[4]  Jing Liu,et al.  Towards a Cohort-Selective Frequency-Compression Hearing Aid , 2004, International Conference on Mathematics and Engineering Techniques in Medicine and Biological Scienes.

[5]  G. E. Peterson,et al.  Control Methods Used in a Study of the Vowels , 1951 .

[6]  T Murry,et al.  Multidimensional classification of normal voice qualities. , 1977, The Journal of the Acoustical Society of America.

[7]  J Jerger,et al.  Comparison of performance with frequency transposition hearing aids and conventional hearing aids. , 1997, Journal of the American Academy of Audiology.

[8]  Robert M. Gray,et al.  An Algorithm for Vector Quantizer Design , 1980, IEEE Trans. Commun..

[9]  Chin-Hui Lee,et al.  On the asymptotic statistical behavior of empirical cepstral coefficients , 1993, IEEE Trans. Signal Process..

[10]  R R Hurtig,et al.  Proportional frequency compression of speech for listeners with sensorineural hearing loss. , 1999, The Journal of the Acoustical Society of America.

[11]  Sara H. Basson,et al.  NTIMIT: a phonetically balanced, continuous speech, telephone bandwidth speech database , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[12]  Jonathan G. Fiscus,et al.  Darpa Timit Acoustic-Phonetic Continuous Speech Corpus CD-ROM {TIMIT} | NIST , 1993 .

[13]  Toby Berger,et al.  Efficient text-independent speaker verification with structural Gaussian mixture models and neural network , 2003, IEEE Trans. Speech Audio Process..

[14]  Roger K. Moore.  Computer Speech and Language , 1986 .

[15]  Norbert Dillier,et al.  Sound Classification in Hearing Aids Inspired by Auditory Scene Analysis , 2005, EURASIP J. Adv. Signal Process..

[16]  Steve Armstrong.  Integrated circuit technology in hearing aids , 2004 .

[17]  J M Kates,et al.  Classification of background noises for hearing-aid applications. , 1995, The Journal of the Acoustical Society of America.

[18]  T. Moon.  The expectation-maximization algorithm , 1996, IEEE Signal Process. Mag..

[19]  Dirk Michaelis,et al.  Acoustic "breathiness measures" in the description of pathologic voices , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[20]  Bhiksha Raj,et al.  Classifier-based non-linear projection for adaptive endpointing of continuous speech , 2003, Comput. Speech Lang..

[21]  M. F. Schwartz,et al.  Identification of speaker sex from isolated, voiceless fricatives. , 1968, The Journal of the Acoustical Society of America.

[22]  G A Studebaker,et al.  Efficacy of 3 commonly used hearing aid circuits: A crossover trial. NIDCD/VA Hearing Aid Clinical Trial Group. , 2000, JAMA.

[23]  Michael J. Carey,et al.  Language independent gender identification , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[24]  Douglas D. O'Shaughnessy,et al.  Robust gender-dependent acoustic-phonetic modelling in continuous speech recognition based on a new automatic male/female classification , 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.