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1 February 1994 Neural network model for isolated-utterance speech recognition
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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.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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