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Speech recognition using filter-bank features

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3 Author(s)
Sourabh Ravindran ; Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA ; Demirogulu, C. ; Anderson, D.V.

Mel-frequency cepstral coefficients (MFCC) have been shown to be very useful in tasks of speech recognition and are the preferred features in state of the art speech recognition systems. The author present features derived from filter bank outputs whose performance is comparable to that of MFCCs for connected digit recognition using a hidden Markov model (HMM) based speech recognition system. The feature extraction method we present is easily implementable in floating gate analog VLSI circuitry which makes it a viable option for low power speech recognition tasks.

Published in:

Signals, Systems and Computers, 2004. Conference Record of the Thirty-Seventh Asilomar Conference on  (Volume:2 )

Date of Conference:

9-12 Nov. 2003

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