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A Speech Enhancement Technique Using Kalman Filter with State Vector of TimeFrequency Patterns
Ryouichi NISHIMURA Futoshi ASANO Yoiti SUZUKI Toshio SONE
Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Vol.E84A
No.4
pp.10271033 Publication Date: 2001/04/01 Online ISSN:
DOI: Print ISSN: 09168508 Type of Manuscript: Special Section PAPER (Special Section on Acoustic Signal Processing) Category: Keyword: speech enhancement, Kalman filter, wavelet transform, timefrequency pattern,
Full Text: PDF>>
Summary:
A new speech enhancement technique is proposed assuming that a speech signal is represented in terms of a linear probabilistic process and that a noise signal is represented in terms of a stationary random process. Since the target signal, i.e., speech, cannot be represented by a stationary random process, a Wiener filter does not yield an optimum solution to this problem regarding the minimum mean variance. Instead, a Kalman filter may provide a suitable solution in this case. In the Kalman filter, a signal is represented as a sequence of varying state vectors, and the transition is dominated by transition matrices. Our proposal is to construct the state vectors as well as the transition matrices based on timefrequency pattern of signals calculated by a wavelet transformation (WT). Computer simulations verify that the proposed technique has a high potential to suppress noise signals.

