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- W2093886330 abstract "This paper describes various speaker normalization and adaptation techniques of a knowledge data base or reference templates to new speakers in automatic speech recognition (ASR). It focuses on a technique for learning spectral transformations, based on a statistical-analysis tool (canonical correlation analysis), to adapt a standard dictionary to arbitrary speakers. The proposed method should permit to improve speaker independence in large vocabulary ASR. Application to an isolated word recognizer improved a 70% correct score to 87%. A dynamic aspect of the speaker adaptation procedure is introduced and evaluated in a particular strategy." @default.
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- W2093886330 date "1986-12-01" @default.
- W2093886330 modified "2023-09-30" @default.
- W2093886330 title "Adaptation of automatic speech recognizers to new speakers using canonical correlation analysis techniques" @default.
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- W2093886330 doi "https://doi.org/10.1016/s0885-2308(86)80017-1" @default.
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