Apparatus and method for speech recognition in the presence of u

Data processing: speech signal processing – linguistics – language – Speech signal processing – Recognition

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704225, 704226, 704233, 704256, G10L 906

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active

057429286

ABSTRACT:
A speech recognition apparatus recognizes utterances of unnatural speech having a higher performance of recognition accuracy with a smaller amount of speech learning data. The speech recognition apparatus includes an acoustic-phonetic variability learn unit, a normal speech model memory, a spectrum smooth-modifier and a speech recognizer. An input speech signal is acoustically analyzed and transformed into a time-series feature vector. The acoustic-phonetic variability learn unit learns an acoustic-phonetic change of spectrum caused by unnatural speech and generates a plurality of acoustic-phonetic variability models. The normal speech model memory stores a normal speech model learned based on normal speech data. The spectrum smooth-modifier modifies the normal speech model based on a plurality of the acoustic-phonetic variability model and generates a plurality of spectrum-modified speech models. The speech recognizer recognizes the time-series feature vector based on the normal speech model and the spectrum-modified speech model.

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Junqua et al."Acoustic and Perceptual Studies of Lombard Speech: Application to Isolated Words Automatic Speech Recognition." ICASSP '90: Acoustics, Speech Signal Processing Conference, 1990.
Hansen, J. "Morphological Constrained Feature Enhancement with Adaptive Cepstral Compensation (MCE-ACC) for Speech Recognition in Noise and Lombard Effect." IEEE Transactions on Speech and Audio Processing, vol. 2, No. 4, Oct. 1994.
Junqua, J. "The Influence of Psychoacoustic and Psycholinguistic factors on Listner Judgments of Intelligibility of Normal and Lombard Speech." ICASSP '91: Acoustics, Speech & Signal Processing Conference, 1991.
Hanson, B. et al. "Robust Speaker-Independent Word Recognition Using Static, Dynamic Acceleration Features: Experiments with Lombard and Noisy Speech." ICASSP '90: Acoustics, Speech & Signal Processing Conference, 1990.
ICSLP 94 "Isolated Word Recognition Using Models for Acoustic Phonetic Variability by Lombard Effect" Suzuki, Nakajima & Abe, Computer & Information Systems Lab., Mitsubishi Electric -Japan.

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