| 摘要 |
PROBLEM TO BE SOLVED: To easily generate a language model (symbol chain probability) used to recognize an input speech in vocal retrieval and reception without generating a text database for its task for recognition. SOLUTION: w<SB>1</SB>to w<SB>N</SB>maximizing equation 1 are found by maximum likelihood estimation and, for example, the appearance probability P(A)=C(A)/Σ<SB>k</SB>(Ck) is found from CA(A)=w<SB>1</SB>×C<SB>1</SB>(A)+, ..., +[w<SB>N</SB>×C<SB>N</SB>(A)] andΣkC(k), where KW is a set of keywords included in a keyword list 150 for a task to be recognized, P<SB>t</SB>(A) the appearance probability of a keyword A in the list 150, P<SB>n</SB>(A) the appearance probability of the word A in a plurality of text databases 160-n (n-1 to N) which are not related directly to the task to be recognized, C<SB>n</SB>(A) an appearance number, andΣ<SB>k</SB>C<SB>n</SB>(k) the total number of words. COPYRIGHT: (C)2004,JPO
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