Abstract
Purpose of speech stream detection is to capture speech stream coming randomly in adverse acoustic environments. A novel robust method for speech stream detection is introduced based on both linear predict code all-pole model and lossless sound tube model to detect speech stream from inputs of wireless speech band communication. It makes use of autocorrelation distribution characteristics of variance sequence of linear predictive residual sequence to formulate two dimensions decision threshold vector. The decision threshold is adaptive to energy of background noise. It can make minimum decisions error. Plenty of signal stream data with various noises under various Signal-to-Noise Ratio and wireless speech band recordings on the spot were used to compare the proposed algorithm respectively with spectrum Entropy and short-time energy algorithm. The experiment results show that the new method for speech stream detection has good detection performance, and it performs well in adverse environments, and the speech stream detected sounds fluently.
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© 2006 Springer-Verlag Berlin Heidelberg
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Nie, Dh., Li, Xy., Zhang, Rb., Xu, D. (2006). Research of a Novel Weak Speech Stream Detection Algorithm. In: Jiao, L., Wang, L., Gao, X., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4222. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881223_74
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DOI: https://doi.org/10.1007/11881223_74
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45907-1
Online ISBN: 978-3-540-45909-5
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