Neural network model for isolated-utterance speech recognition

Jung H. Kim; Thomas Ervin; Evi H. Park; Celestine A. Ntuen; Shiu M. Cheung; Wagih H. Makky

doi:10.1117/12.172532

1 February 1994 Neural network model for isolated-utterance speech recognition

Jung H. Kim, Thomas Ervin, Evi H. Park, Celestine A. Ntuen, Shiu M. Cheung, Wagih H. Makky

Proceedings Volume 2093, Substance Identification Analytics; (1994) https://doi.org/10.1117/12.172532
Event: Substance Identification Technologies, 1993, Innsbruck, Austria

Abstract

Speech recognition by machine has finally come of age in a practical sense. A major problem in speech recognition, however, stems from the large variance of different utterances for the same word. This paper proposes an efficient method of achieving high accuracy speaker- independent isolated-word recognition through the implementation of associative memories and neural networks. The basic architecture of such a process involves two-stages: speech analysis and recognition.

Citation Download Citation

Jung H. Kim, Thomas Ervin, Evi H. Park, Celestine A. Ntuen, Shiu M. Cheung, and Wagih H. Makky "Neural network model for isolated-utterance speech recognition", Proc. SPIE 2093, Substance Identification Analytics, (1 February 1994); https://doi.org/10.1117/12.172532

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