6 April 1995 Real-world speech recognition with neural networks
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Abstract
We describe a system based on neural networks that is designed to recognize speech transmitted through the telephone network. Context-dependent phonetic modeling is studied as a method of improving recognition accuracy, and a special training algorithm is introduced to make the training of these nets more manageable. Our system is designed for real-world applications, and we have therefore specialized our implementation for this goal; a pipelined DSP structure and a compact search algorithm are described as examples of this specialization. Preliminary results from a realistic test of the system (a field trial for the U.S. Census Bureau) are reported.
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Etienne Barnard, Etienne Barnard, Ronald Cole, Ronald Cole, Mark Fanty, Mark Fanty, Pieter J. E. Vermeulen, Pieter J. E. Vermeulen, } "Real-world speech recognition with neural networks", Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); doi: 10.1117/12.205157; https://doi.org/10.1117/12.205157
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