Presentation 2011-12-19
A study on language identification using non-negative matrix factorization as an extractor of phonotactic information
Tsuyoshi OGATA, Kazuyuki TAKAGI,
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Abstract(in English) Language identification is the technique to identify the language being spoken by an unknown speaker. In this paper, phonotactic information was used as the feature for language identification. In order to obtain phonotactic information, it is required to extract the phoneme sequence from speech data. A template-based non-negative matrix factorization was applied for this purpose. The extracted phoneme sequence was then analyzed to yield n-gram models which may reflect the order in which the phoneme-like categories of speech occur in the language. Language identification was carried out by a support vector machine with the n-gram as the feature vector. It is shown that the identification performance changes with the number of spectrum templates and the order of n-gram, and that the best performance of 98.6% was obtained when the number of spectrum was 13 and the order of n-gram was 3.
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Keyword(in English) language identification / non-negative matrix factorization / support vector machine
Paper # NLC2011-38,SP2011-83
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Committee NLC
Conference Date 2011/12/12(1days)
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Registration To Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A study on language identification using non-negative matrix factorization as an extractor of phonotactic information
Sub Title (in English)
Keyword(1) language identification
Keyword(2) non-negative matrix factorization
Keyword(3) support vector machine
1st Author's Name Tsuyoshi OGATA
1st Author's Affiliation The University of Electro-Communications()
2nd Author's Name Kazuyuki TAKAGI
2nd Author's Affiliation The University of Electro-Communications
Date 2011-12-19
Paper # NLC2011-38,SP2011-83
Volume (vol) vol.111
Number (no) 364
Page pp.pp.-
#Pages 4
Date of Issue