From ear modeling to auditory transform

• Autorzy: Kleczkowski, P.
• Języki publikacji: EN

Abstrakty

EN

Understanding how the auditory system works recently gains increasing importance in audio engineering. Its most widespread practical use is in perceptual audio coders, with even more applications to be foreseen in the future. The construction of a mathematical procedure that could transform acoustic signals heard by humans to data corresponding to auditory sensation would open way to significant progress in audio engineering. In this paper the issue is discussed and important research in the field is reviewed. The proposal for a frequency analysis procedure appropriate for ear modeling is presented and verified. This procedure is a form of the Wavelet Transform.

• Czasopismo: Archives of Acoustics
• Rocznik: 1999
• Tom: Vol. 24, no. 2
• Strony: 191-206
• Opis fizyczny: Bibliogr. 46 poz., rys., wykr.

Twórcy

autor

Kleczkowski, P.

• Department of Mechanics and Vibroacoustics, Academy of Mining and Metallurgy Poland,

Bibliografia

• [1] A.N. Akansu, M.J.T. Smith [Eds.], Subband and wavelet transforms, Kluwer, Boston 1996.
• [2] M. Bobrek, D.B. Koch, Music segmentation using tree-structured filter banks, Journal of the Audio Engineering Society, 46, 5, 413-427 (1998).
• [3] E. DE Boer, Classical and non-classical models of the cochlea, J.A.S.A., 101, 4, 2148-2150 (1997).
• [4] J.C . Brown, Calculation of a constant Q spectral transform, J.A.S.A., 89, 1, 425-434 (1990).
• [5] C.S. Burrus, R.A. Gopinath, H. Guo, Introduction to wavelets and wavelet transforms, Prentice Hall, Upper Sadie River, NJ 1998.
• [6] Y.T. Chan, lYauelet basics, Kluwer Academic Press, Norwell 1995.
• [7] L. Cohen, Time-frequency analysis, Prentice Hall, Englewood Cliffs, NJ 1995.
• [8] M.A. Cohen, S. Grossberg, L.L. Wyse, A spectral network model of pitch perception, J.A.S.A., 98, 2, 862-885 (1995).
• [9] A. Czyżewski, New learning algorithms for the processing of old audio recordings, 99th A.E.S Convention, Preprint no. 4078, New York 1995.
• [10] I. Daubechies, The wavelet transform, time-frequency localization and signal analysis, IEEE Transaction on Information Theory, 36, 5, 961-1005 (1990).
• [11] Z. Engel, Ochrona środowiska przed drganiami i hałasem, Wydawnictwo Naukowe PWN, Warszawa 1993.
• [12] J.L. Flanagan, Models lo r approximating basilar membrane displacement, The Bell System Tech¬nical Journal, 1163-1191 (1960).
• [13] L.C. Gresham, L.M. Collins, Analysis of the performance of a model-based optimal auditory signal processor, J.A.S.A., 103, 5, 2520-2529 (1998).
• [14] F.J . Harris, On the use of windows for harmonic analysis with the discrete Fourier transform, Proceedings of the IEEE, 66, 1, 51-83 (1978).
• [15] W.M. Hartmann, Pitch, periodicity, and auditory organization, J.A.S.A., 100, 6, 3491-3502 (1996).
• [16] W. Heinbach, Aurally adequate signal representation: The part-ton e-tim e-pattern , Acustica, 67, 113-120 (1988).
• [17] T. Irino, A “Gammachirp” function as an optimal auditory filter with the Mellin transform, Proc. IEE E Int. Conf, on Acoustics, Speech and Signal Processing, 981-984, Atlan ta 1996.
• [18] T. Irino, II. Kawahara, Signal reconstruction from modified auditory wavelet transform, IEEE Trans. on Signal Processing, 41, 12, 3549-3554 (1993).
• [19] T. Irino. R..D. Patterson, A time domain, level dependent auditory filter: The gammachirp, J.A.S.A., 101, 1, 412-419 (1997).
• ]20] J.M. Kates, A time-domain digital Cochlear model, IEEE Trans, on Signal Processing, 39, 12, 2573-2592 (1991).
• [21] D.O. Kim, C.E. Molnar, R.R. Pfeiffer, A system of nonlinear differential equations modeling basilar-membrane motion, J.A.S.A ., 54, 6, 1517-1529 (1973).
• [22] P. Kleczkowski, Nowy sposób kodowania parametrów dla syntezy addytywnej sygnałów, Mat. VII Sympozjum Inżynierii i Reżyserii Dźwięku, 125-128, Kraków 1997.
• [23] J. Kovacevic, M. VET TE RLI, Wavelets and subband coding, Prentice Hall, Englewood Cliffs 1995.
• [24] R.F. Lyon, An analog electronic cochlea, IEEE Trans, on A.S.S.P., 36, 7, 1119-1133 (1988).
• [25] II.S. Malvar, Signal processing with lapped transforms, Artech House, Boston 1992.
• [26] R. J. McAulay, T .F. Quatieri, Speech analysis/synthesis based on a sinusoidal representation, IEEE Trans, on A.S.S.P., 34, 4, 744-754 (1986).
• [27] R. Meddis, M.J. Hewitt, Virtual pitch and phase sensitivity o f a computer model of the auditory periphery. I. Pitch identification, J.A.S.A ., 89, 6, 2866-2882 (1991).
• [28] B.C. Moore [Ed.], Frequency selectivity in hearing, Academic Press, London 1986.
• [29] S.H. Nawab, Short-time Fourier transform, [in:] J.S. Lim, A.V. Oppenheim [Eds.], Advanced Topics in Signal Processing, Pren tice Hall, Englewood Cliffs, NJ 1988.
• [30] B. Paillard, P. Mabilleau, S. Morisette, J. Soumagne, PERCEVAL: Perceptual evaluation of the quality of audio signals, Journal of the Audio Engineering Society, 40, 1/2, 21-31 (1992).
• [31] R.D. Patterson, Auditory filter shapes derived with noise stimuli, J.A .S.A ., 59, 3, 640-654 (1976).
• [32] W.J. Pielemeier, G.H. Wakefield, A high resolution time-frequency representation for musical instrument signals, J.A.S.A ., 99, 4, 2382-2396 (1996).
• [33] J.-C . Risset, D.L. Wessel, Exploration of timbre by analysis and synthesis, [in:] The psychology of Music, D. Deutsch [Ed.], Academic Press, New York 1982, 26-58.
• [34] M.R. Schroeder, J.L . Hall, Model for mechanical to neural transduction in the auditory recep¬tor, J.A.S.A ., 55, 5, 1055-1060 (1974).
• [35] S. Shlien, The modulated lapped transform, its time-varying forms , and its applications too, udiocoding standards, IEE E Trans, on Speech and Audio Proc., 5, 4, 359-366 (1997).
• [36] M. Slaney, Pattern playback in the ’90s, [in:] Advances in Neural Processing Systems 7, G. Tesauro, D. Touretzky, T. Leen [Eds.], Morgan Kaufmann Publishers, San Mateo, CA, 1995.
• [37] T. Sporer, K. Brandenburg, Constraints of filter banks used for perceptual measurement, J.A.E.S ., 43, 3, 107-116 (1995).
• [38] G. Strang, T. Nguyen, Wavelets and filter banks, Wellesley - Cambridge Press, New York 1996.
• [39] R. Tadeusiewicz, Sygnał mowy, WKiŁ, Warszawa 1988.
• [40] P.P . Vaidyanathan, Multirate systems and filter banks, Prentice Hall, Englewood Cliffs, NJ 1993.
• [41] X. Yang, K. Wang, S. Shamma, Auditory representations of acoustic signals, IEEE Trans, on Information Theory, 38, 2, 824-839 (1992).
• [42] K. Wang, S. Shamma, Self-normalizątion and noise-robustness in early auditory representations, IEEE Trans, on Speech and Audio Processing, 2, 3, 421-435, July 1994.
• [43] K. Wang, S. Shamma, Spectral shape analysis in the central auditory system, IEEE Trans, on Speech and Audio Processing, 3, 5, 382-395 (1995).
• [44] M.V. Wickerhauser, Adapted wavelet analysis from theory to software, IEEE Press, Piscataway, NJ 1994.
• [45] E. Zwicker, H. Fastl, Psychoacoustics, facts and models, Springer-Verlag, Berlin 1990.
• [46] E. Zwicker, T. Zwicker, Audio engineering and psychoacoustics: Matching signals to the final receiver, the human auditory system, J.A.E.S., 39, 3, 115-125 (1991).