NDLI: A training procedure for isolated word recognition systems

Content Provider	IEEE Xplore Digital Library
Author	Furui, S.
Copyright Year	1974
Abstract	A procedure has been devised to reduce the amount of training required for a phoneme-based speaker-dependent word recognition system and still maintain performance. Each new speaker is required to provide utterances of only a fraction of the entire vocabulary as a training set. A set of transformation rules is used to estimate phoneme templates for the entire vocabulary from phoneme templates included in the training. The transformation rules are obtained in a pretraining procedure in which a group of speakers provides utterances of the entire vocabulary and multiple regression analysis (MRA) is used to obtain linear estimates of the entire phoneme template set in terms of the set designated as training templates. This group of speakers is generally distinct from the group of training speakers. Thus, since the transformation rules are established independent of the training speakers, the entire procedure can be considered a hybrid speaker-dependent/ speaker-independent system. Results of recognition experiments using spoken digits uttered by 30 male and female speakers and 67 airport names uttered by 30 male speakers have ascertained the effectiveness of this training procedure. A mean recognition accuracy of 98.2 percent was obtained for the latter utterance set after a 12-word training procedure.
Starting Page	129
Ending Page	136
Page Count	8
File Size	817692
File Format	PDF
ISSN	00963518
Volume Number	28
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1980-04-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vocabulary Airports Speech recognition Acoustic measurements Speech processing Regression analysis Automatic speech recognition System testing Telegraphy Telephony
Content Type	Text
Resource Type	Article
Subject	Signal Processing

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