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Speech recognition method using speaker cluster models

  • US 6,567,776 B1
  • Filed: 04/04/2000
  • Issued: 05/20/2003
  • Est. Priority Date: 08/11/1999
  • Status: Expired due to Term
First Claim
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1. A speech recognition method comprising:

  • receiving a speech signal;

    recognizing the speech signal using a speaker cluster model obtained in a training phase wherein the speaker cluster model is a collection of a plurality of cluster-dependent models, and a score of each candidate is calculated according to a score function which is defined by taking the dependency among the cluster-dependent models into account; and

    obtaining a final recognition result according to a decision rule based on the Score of each candidate, wherein the training phase comprises building an initialization model, and adjusting parameters of at least two cluster-dependent models of the initialization model by using a discriminative training method to obtain the speaker cluster model wherein the discriminative training method is implemented by using a minimum classification error as a training criterion, a discriminant function of the discriminative training method being defined in the same manner as the score function, and the score function is defined as;

    gi

    (X;

    Γ

    )
    =log



    [1N



    n=1N






    wn

    (X)






    exp



    [hi

    (X;

    Λ

    n
    )


    ξ

    ]
    ]
    1ξ

    ,i=1,2,





    ,M
    embedded image

    wherein gi(X;

    Ã

    ) is the score function, X is a feature vector sequence of the speech signal, Ã

    represents an entire parameter set of the speaker cluster model, N is the number of cluster-dependent models, parameter sets corresponding to the N cluster-dependent models are Ë

    1, Ë

    2, . . . , Ë

    N, M is the number of candidates to be classified, hi(X;

    Ë

    n) is a log-likelihood function defined only on a parameter set Ë

    n, î

    is a positive weighting number, and wn(X) is a cluster weighting function that indicates the degree to which the nth cluster-dependent model is used for recognition.

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