Noise adaptation system of speech model, noise adaptation method, and noise adaptation program for speech recognition

An adaptive system and noise technology, applied in speech recognition, speech analysis, instruments, etc., can solve problems such as characteristic deviation of noise
CN1542737AInactive Publication Date: 2004-11-03NTT DOCOMO INC +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
NTT DOCOMO INC
Publication Date
2004-11-03
Estimated Expiration
Not applicable · inactive patent

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Abstract

An object of the present invention is to enable optimal clustering for many types of noise data and to improve the accuracy of estimation of a speech model sequence of input speech. Noise is added to speech in accordance with noise-to-signal ration conditions to generated noise-added speech (step S1), the mean value of speech cepstral is subtracted from the generated, noise-added speech (step S2), a Gaussian distribution model of each piece of noise-added speech is created (step S3), the likelihoods of the pieces of noise-added speech are calculated to generate a likelihood matrix (step S4) to obtain a clustering result. An optimum model is selected (step S7) and linear transformation is performed to provide a maximized likelihood (step S8). Because noise-added speech is consistently used both in clustering and model learning, clustering for many types of noise data and an accurate estimation of a speech model sequence can be achieved.
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Description

technical field

[0001] The invention relates to a speech model noise adaptive system, a noise adaptive method and a speech recognition noise adaptive program. Specifically, the present invention relates to adapting a clean speech model generated by modeling speech features using a Hidden Markov Model (HMM) with the noisy speech to be recognized, thereby improving speech recognition in noisy environments. Speech model noise adaptive system, noise adaptive method and speech recognition noise adaptive program of the recognition rate. Background technique

[0002] A tree-structured piecewise linear transformation method is described in Non-Patent Document 1 below. According to the method disclosed in this document, the noise is clustered, and according to the result of the clustering, a tree structure noisy speech model space is produced, and the speech feature parameters of the input noisy speech to be recognized are extracted, from the tree structure The optimal model is sel...

Claims

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