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    • 1. 发明授权
    • Method for the composition of noise-resistant hidden markov models for
speech recognition and speech recognizer using the same
    • 用于语音识别和语音识别器的噪声抵抗隐马尔可夫模型的组合方法
    • US5721808A
    • 1998-02-24
    • US610614
    • 1996-03-04
    • Yasuhiro MinamiTomoko MatsuiSadaoki Furui
    • Yasuhiro MinamiTomoko MatsuiSadaoki Furui
    • G10L15/14G10L15/20G10L5/06
    • G10L15/20G10L15/144
    • Noise-resistant speech HMMs are composed by: recording noise in the environment of utterance (S.sub.1); preparing HMMs of the noise (S.sub.2); transforming the output probability distribution of each of the noise HMMs and speech HMMs prepared from speech unaffected by noise and multiplicative distortion to a linear spectral domain (S.sub.31); multiplying the speech HMM distribution in the linear spectral domain by a multiplicative distortion W that is an unknown variable (S.sub.321); convoluting the multiplied value and the noise HMM distribution in the linear spectral domain (S.sub.322); inversely transforming the convoluted value to the original domain of the speech HMM (S.sub.33) to compose incomplete noise-resistant speech HMMs each containing multiplicative distortion as an unknown variable (S.sub.3); calculating the likelihoods of the incomplete noise-resistant speech HMMs for input speech and estimating the multiplicative distortion of that one of the incomplete noise-resistant HMMs which has the maximum likelihood (S.sub.4); and substituting the estimated value into the incomplete noise-resistant speech HMMs (S.sub.5).
    • 抗噪声语音HMM由以下内容组成:在语音环境中记录噪声(S1); 准备HMM的噪声(S2); 将由不受噪声和乘法失真影响的语音准备的每个噪声HMM和语音HMM的输出概率分布变换为线性频域(S31); 将线性频域中的语音HMM分布乘以作为未知变量的乘法失真W(S321); 在线性谱域中卷积乘法值和噪声HMM分布(S322); 将卷积值逆向变换为语音HMM的原始域(S33),以构成每个包含乘法失真的不完整的抗噪声语音HMM作为未知变量(S3); 计算用于输入语音的不完整的抗噪声语音HMM的可能性,并估计具有最大似然性的不完全抗噪声HMM中的一个的乘法失真(S4); 并将估计值代入不完整的抗噪声语音HMM(S5)。