Data processing: speech signal processing – linguistics – language – Linguistics – Natural language
Reexamination Certificate
1998-12-07
2001-11-13
Edouard, Patrick N. (Department: 2744)
Data processing: speech signal processing, linguistics, language
Linguistics
Natural language
C704S255000
Reexamination Certificate
active
06317707
ABSTRACT:
BACKGROUND
The present invention relates to an application that builds linguistic models from a corpus of speech.
For a machine to comprehend speech, not only must the machine identify spoken (or typed) words, but it also must understand language grammar to comprehend the meaning of commands. Accordingly, much research has been devoted to the construction of language models that a machine may use to ascribe meaning to spoken commands. Often, language models are preprogrammed. However, such predefined models increase the costs of a speech recognition system. Also, the language models obtained therefrom have narrow applications. Unless a programmer predefines the language model to recognize a certain command, the speech recognition system that uses the model may not recognize the command. What is needed is a training system that automatically extracts grammatical relationships from a predefined corpus of speech.
SUMMARY
An embodiment of the present invention provides a method of learning grammar from a corpus, in which context words are identified from a corpus. For the other non-context words, the method counts the occurrence of predetermined relationships with the context words, and maps the counted occurrences to a multidimensional frequency space. Clusters are grown from the frequency vectors. The clusters represent classes of words; words in the same cluster possess the same lexical significancy and provide an indicator of grammatical structure.
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Bangalore Srinivas
Riccardi Giuseppe
AT&T Corp.
Edouard Patrick N.
Kenyon & Kenyon
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