Automatic Recognition of Spoken English Words.
TEXAS UNIV AUSTIN ELECTRONICS RESEARCH CENTER
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The object of the research was the development and testing of techniques for use in the recognition of spoken words. A trainable pattern classifier to recognize a limited vocabulary of spoken words was implemented using these techniques. The words used were spoken into a microphone located on the operator console in the Hybrid Computing Facility. Speech samples were processed by a 31-channel bandpass filterbank before digitization. Training was accomplished by first segmenting each spoken word into three time sections and then performing clustering operations on these segments to derive a set of prototype segments, along with estimated a priori probabilities of occurrence for these prototypes. The system was trained first on a single speaker and later on a group of five speakers, using the digitszerothroughnineas a test vocabulary. Recognition rates were generally from 94 to 98 on new data by the speakers for which the system was trained. Author Modified Abstract
- Non-Radio Communications