Real-world speech recognition with neural networks
Etienne Barnard, Ronald A. Cole, Mark Fanty, Pieter J. E. Vermeulen · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1995
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.