NDLI: Some experiments in automatic recognition of a thousand word vocabulary

Content Provider	IEEE Xplore Digital Library
Author	Mari, J. Haton, J.
Copyright Year	1984
Description	Author affiliation: University of Nancy 1, Vandoeuvre, France (Mari, J.)
Abstract	Our group has been designing for the past twelve years several speech recognition systems, from isolated vocabulary pattern matching systems to continuous speech understanding systems. The experiments we carried out showed us that the systems designed for restricted vocabularies task were not readily extensible to large vocabularies. We therefore started some years ago implementing a 200 word recognition system using a phonetic approach. This system was tested successfully in 1980. In continuation of this research we decided to extend our approach to a 1000 word vocabulary. This paper describes the principles involved in this system together with the preliminary results already obtained. The basic idea is to reduce the number of word candidates for the recognition by looking for robust phonetic features computed from the input signal. These features are used as a key for accessing the lexicon. Since the determination of the features is carried out in parallel with the phonetic decoding of the input word, it is possible to design a multiprocessor structure in order to reduce the overall recognition time. The determination of crude phonetic features is described together with the organization of the lexicon. Some preliminary results are finally presented and discussed.
Starting Page	397
Ending Page	400
File Size	87838
Page Count	4
File Format	PDF
DOI	10.1109/ICASSP.1984.1172526
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1984-03-19
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vocabulary Pattern matching Decoding Pattern recognition Artificial intelligence Speech recognition System testing Robustness Application software Natural languages
Content Type	Text
Resource Type	Article

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