Abstract
The analysis of the speech signal using wavelet packet trees (WPT) is a very flexible tool, capable of effectively manipulate the frequency subbands thanks to the orthonormal bases it provides. Here, dimension reduction becomes very important since the number of subbands grows exponentially with the level of decomposition, and their discriminative relevancy is different, which leads to different resolution for each one. A method based on mutual information is proposed in order to keep as much discriminative information as possible and the less amount of redundant information.
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References
Campbell Jr., J.P.: Speaker recognition: a tutorial. Proceedings of the IEEE 85(9), 1437–1462 (1997)
Kinnunen, T.: Spectral Features for Automatic Text-Independent Speaker Recognition. Licentiate’s thesis, University of Joensuu, Department of Computer Science, Joensuu, Finland (2004)
Sarikaya, R., Hansen, H.L.: High resolution speech feature parametrization for monophone-based stressed speech recognition. IEEE Signal Processing Letters 7(7), 182–185 (2000)
Farooq, O., Datta, S.: Mel-scaled wavelet filter based features for noisy unvoiced phoneme recognition. In: International Conference on Spoken Language Processing ICSLP, pp. 1017–1020 (2002)
Goswami, J.C., Chan, A.K.: Fundamentals of Wavelets: Theory, Algorithms, and Applications. John Wiley & Sons, Chichester (1999)
Mallat, S.: A wavelet tour of signal processing. Academic Press, San Diego (1998)
Battle, G.: A block spin construction of ondelettes. Part I: Lemarié functions. Comm. Math. Phys. 110, 601–615 (1987)
Lemarié, P.G.: Ondelettes à localisation exponentielle. J. Math. Pures Appl. 67, 227–236 (1988)
Siafarikas, M., Ganchev, T., Fakotakis, N.: Wavelet Packet Based Speaker Verification. In: Ortega-Garcia, J., et al. (eds.) The Speaker and Language Recognition Workshop ODYSSEY (2004)
Cover, T.M., Thomas, J.A.: Elements of Information Theory. Wiley-Interscience, Chichester (1991)
Peng, H.C., Long, F., Ding, C.: Feature selection based on mutual information: Criteria of Maxdependency, Max-relevance and Min-redundancy. IEEE Trans. On Pattern Analysis and Machine Intelligence 27(8), 1226–1238 (2005)
Lu, X., Dang, J.: Dimension reduction for speaker identification based on mutual information. In: Interspeech, pp. 2021–2024 (2007)
Ortega-Garcia, J., Gonzalez-Rodriguez, J., Marrero-Aguiar, V.: AHUMADA: A large speech corpus in Spanish for speaker characterization and identification. Speech Comm. 31, 255–264 (2000)
Fletcher, H.: Auditory patterns. Reviews of Modern Physics 12, 47–65 (1940)
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Fernández, R., Montalvo, A., Calvo, J.R., Hernández, G. (2008). Selection of the Best Wavelet Packet Nodes Based on Mutual Information for Speaker Identification. In: Ruiz-Shulcloper, J., Kropatsch, W.G. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2008. Lecture Notes in Computer Science, vol 5197. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85920-8_10
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DOI: https://doi.org/10.1007/978-3-540-85920-8_10
Publisher Name: Springer, Berlin, Heidelberg
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