Data processing: speech signal processing – linguistics – language – Speech signal processing – Recognition
Reexamination Certificate
2008-09-09
2008-09-09
Abebe, Daniel D (Department: 2626)
Data processing: speech signal processing, linguistics, language
Speech signal processing
Recognition
C704S251000
Reexamination Certificate
active
10920461
ABSTRACT:
An object of the present invention is to facilitate dealing with noisy speech with varying SNR and save calculation costs by generating a speech model with a single-tree-structure and using the model for speech recognition.Every piece of noise data stored in a noise database is used under every SNR condition to calculate the distance between all noise models with the SNR conditions and the noise-added speech is clustered. Based on the result of the clustering, a single-tree-structure model space into which the noise and SNR are integrated is generated (steps S1to S5). At a noise extraction step (step S6), inputted noisy speech to be recognized is analyzed to extract a feature parameter string and the likelihoods of HMMs are compared one another to select an optimum model from the tree-structure noisy speech model space (step S7). Linear transformation is applied to the selected noisy speech model space so that the likelihood is maximized (step S8).
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Furui Sadaoki
Horikoshi Tsutomu
Sugimura Toshiaki
Zhang Zhipeng
Abebe Daniel D
Sadaoki Furui and NTT DoCoMo, Inc.
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