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    • 7. 发明授权
    • Noise adaptation system of speech model, noise adaptation method, and noise adaptation program for speech recognition
    • 语音模型噪声适应系统,噪声适应方法和语音识别噪声适应程序
    • US07552049B2
    • 2009-06-23
    • US10796283
    • 2004-03-10
    • Zhipeng ZhangKiyotaka OtsujiToshiaki SugimuraSadaoki Furui
    • Zhipeng ZhangKiyotaka OtsujiToshiaki SugimuraSadaoki Furui
    • G10L15/00
    • G10L15/20
    • 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 ratio conditions to generate noise-added speech (step S1), the mean value of speech cepstral is subtracted from the generated, noise-added speech (step 2), 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.
    • 本发明的一个目的是为多种类型的噪声数据实现最佳聚类,并提高输入语音的语音模型序列的估计精度。 根据噪声信号比率条件将噪声添加到语音中以产生噪声添加语音(步骤S1),从产生的噪声添加语音(步骤2)中减去语音倒频谱的平均值,高斯分布 创建每个噪声添加语音的模型(步骤S3),计算噪声添加语音片段的可能性,以生成似然矩阵(步骤S4)以获得聚类结果。 选择最佳模型(步骤S7),并执行线性变换以提供最大似然(步骤S8)。 因为在聚类和模型学习中始终使用增加噪音的语音,所以可以实现许多类型的噪声数据的聚类和语音模型序列的精确估计。