Title :
Speech recognition using filter-bank features
Author :
Ravindran, Suurabh ; Demirogulu, C. ; Anderson, David F.
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
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.
Keywords :
VLSI; analogue integrated circuits; band-pass filters; cepstral analysis; channel bank filters; feature extraction; hidden Markov models; speech recognition; HMM; Mel-frequency cepstral coefficient; connected digit recognition; feature extraction; filter-bank output features; floating gate analog VLSI circuitry; hidden Markov model; speech recognition system; Cepstral analysis; Channel bank filters; Decorrelation; Filter bank; Finite impulse response filter; Hidden Markov models; Linear predictive coding; Nonlinear filters; Speech recognition; Very large scale integration;
Conference_Titel :
Signals, Systems and Computers, 2004. Conference Record of the Thirty-Seventh Asilomar Conference on
Print_ISBN :
0-7803-8104-1
DOI :
10.1109/ACSSC.2003.1292312
