Title :
A phoneme-similarity based ASR front-end
Author :
Applebaum, T.H. ; Morin, P. ; Hanson, B.A.
Author_Institution :
Speech Technol. Lab., Panasonic Technol. Inc., Santa Barbara, CA, USA
Abstract :
A training procedure for phoneme similarity reference models is described and two word recognition methods based on phoneme similarities for the English language are evaluated under clean, noisy and channel-distorted speech conditions. Optimization of recognition performance is examined in terms of multi-style training, cepstral normalizations, gender dependent models and length of time over which the phoneme similarities are computed. Phoneme similarities provide a compact speech representation which is relatively insensitive to the variations between speakers
Keywords :
acoustic signal processing; cepstral analysis; natural languages; noise; signal representation; speech processing; speech recognition; ASR front-end; English language; acoustic analysis; automatic speech recognition front-end; cepstral normalizations; channel-distorted speech; clean speech; compact speech representation; gender dependent models; multistyle training; noisy speech; phoneme similarity reference models; recognition performance optimisation; training procedure; word recognition methods; Automatic speech recognition; Cepstral analysis; Covariance matrix; Databases; Distributed computing; Hidden Markov models; Natural languages; Speech analysis; Speech recognition; Vectors;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-3192-3
DOI :
10.1109/ICASSP.1996.540283
