Abstract
Speech technology is one of the key technical issues involved in Information Technology as it constitutes an important aspect of Human Computer Interaction. Prediction of speech signal has applications in speech technology, especially in coding. Conventionally, linear prediction is used. However, non-linear phenomena exist in speech production and, considering this non-linearity should lead to lower signal dynamics during coding with a consequent reduction in bit-rate and the needed bandwidth. The non-linear prediction of speech segments, as long as a whole vowel, using neural nets is studied in this paper. It is shown that non-linear speech prediction does not lead to an appreciable further reduction in the residual signal in this case.
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References
H.M. Teager: Some Observations on Oral Air Flow Vocalization, IEEE Trans. ASSP, Vol. 28(5), PP 599–601
N. Tishby: A dynamical systems approach to speech processing, Proc. ICASSP, 1990, PP365–368
B. Townshend: Non-linear prediction of speech, Proc. ICASSP, 1991, PP 425–428
G. DAlessandro etal.: A new sub-band non-linear prediction coding algorithm for narrowband speech signal-The NADPCMB-MLT coding scheme, Proc. ICASSP, 2002, (NEURAL-L03, paper 2066)
A.S. Weigend: Time Series Analysis and Prediction, http://www.cs.colorado.edu/~andreas/home.html
T. Masters: Signal and Image Processing with Neural Networks, John Wiley & Sons (1994)
N.K. Bose & P. Liang: Neural Network Fundamentals with Graphs, Algorithms and Applications, Mc Graw Hill (1996)
Limin Fu: Neural Network in Computer Intelligence, Mc Graw Hill (1994)
D.P. Mandic & J.A. Chambers: Recurrent Neural Networks for Prediction: Learning Algorithms, Architectures and Stability, John Wiley & Sons (2001)
F.J. Pineda, Generalization of Back Propagation to Recurrent Neural Networks, Physics Review Letters, 59, PP 2229–2232
MATLAB NN Toolbox User’s Guide; The MATH WORKS INC, http://www.mathworks.com
S. Haykin & S. Kesler, Prediction Error Filtering and Maximum Entropy Spectral Estimation, in Non-linear Methods of Spectral Analysis, Springer-Verlag (1983)
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Ashouri, K., Amini, M., Savoji, M.H. (2002). Non-linear Prediction of Speech Signal Using Artificial Neural Nets. In: Shafazand, H., Tjoa, A.M. (eds) EurAsia-ICT 2002: Information and Communication Technology. EurAsia-ICT 2002. Lecture Notes in Computer Science, vol 2510. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36087-5_25
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DOI: https://doi.org/10.1007/3-540-36087-5_25
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