In this paper we present a new speech recognition strategy that is based on diphones as the primary recognition unit in a time-event neural network (TENN) ...
Both of these techniques improved recognition accuracy on male and female speech samples from all eight dialect regions in the U.S. In one test set, frequency ...
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Jun 13, 1996 · During word recognition tests, the correct word was detected 85% of the time in continuous speech. Of those detections, the correct diphone was ...
We describe a system based on neural networks that is designed to recognize speech transmitted through the telephone network. Context-dependent phonetic ...
Diphone-based Speech Recognition using Time-Event Neural Networks-book.
Diphone-based Speech Recognition using Time-Event Neural Networks · Julkaisut · Diphone-based Speech Recognition using Time-Event Neural Networks ...
Neural networks have been shown to be a powerful approach to speech recognition. Especially the class of time-delay neural networks (TDNN) exhibiting a time ...
This paper describes a system that uses a time-delay neural network (TDNN) to perform this phonetic-to-acoustic mapping, with another neural network to control ...
A Diphone-Based Digit Recognition System Using Neural Networks | PDF
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This document describes a diphone-based digit recognition system using neural networks as an alternative to traditional monophone, biphone, and triphone-based ...
Using techniques based on data mining and statistical analysis, machine learning allows computers to emulate human learning behavior, rea- soning and decision ...