Improvement on speech recognition and synthesis for disabled individuals using fuzzy neural net retrofits
- 1 January 1988
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 251-258 vol.2
- https://doi.org/10.1109/icnn.1988.23936
Abstract
Currently available voice input-output technology for microcomputers is reviewed. It is found that although such devices can be adequate in the case of voice output, voice input technology is far inferior; its deficiencies include user dependence, need for extensive user involvement in the training process, limited vocabulary, inability to recognize connected or continuous speech adequately, and high costs. The requirements for an adequate speech input device are briefly outlined and currently available applicable technologies are noted. An interactive learning system that uses off-the-shelf technology is described. The system involves three stages: dynamic word wrap matching is used to detect and align candidate words; fuzzy neural-net word recognition is applied to input spectrogram patterns; a voice synthesizer is used to complete the interactive loop. The system has a recognition accuracy of 95-98%.<>Keywords
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