Foreground auditory scene analysis for hearing aids

Although a wide variety of signal enhancement algorithms are available for hearing aids, selection and parameterization of the best algorithm at any given time is highly dependent upon the environment of the hearing aid user. The use of auditory scene analysis has been proposed by several groups to categorize the background noise. In this work, an algorithm is proposed to categorize a foreground speaker as opposed to the background noise and parameterize a frequency-based compression algorithm which has been previously shown to improve speech understanding for some individuals with severe sensorineural hearing loss in the 2-3kHz range.

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

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

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

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

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

[6]  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.

[7]  D. Rendall,et al.  Pitch (F0) and formant profiles of human vowels and vowel-like baboon grunts: the role of vocalizer body size and voice-acoustic allometry. , 2005, The Journal of the Acoustical Society of America.

[8]  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).

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

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

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

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

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

[14]  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.

[15]  Bernard Widrow,et al.  Special Issue on Speech Processing for Hearing Aids , 2003, Speech Commun..

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

[17]  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.

[18]  George Tzanetakis,et al.  Musical genre classification of audio signals , 2002, IEEE Trans. Speech Audio Process..

[19]  D D Dirks,et al.  Evaluation of hearing-impaired listeners using a Nonsense-Syllable Test. I. Test reliability. , 1982, Journal of speech and hearing research.

[20]  Douglas A. Reynolds,et al.  Comparison of background normalization methods for text-independent speaker verification , 1997, EUROSPEECH.

[21]  Enrico Bocchieri,et al.  Vector quantization for the efficient computation of continuous density likelihoods , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[22]  Jing Liu,et al.  Audio scene analysis as a control system for hearing aids , 2005, Seventh IEEE International Symposium on Multimedia (ISM'05).

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

[24]  Jan P. H. van Santen,et al.  Strong interaction between factors influencing consonant duration , 1997, EUROSPEECH.

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

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

[27]  Liming Chen,et al.  Voice-Based Gender Identification in Multimedia Applications , 2005, Journal of Intelligent Information Systems.

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

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

[30]  Robert V. Hogg,et al.  Introduction to Mathematical Statistics. , 1966 .

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