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A method for noise adaptation by means of a transformed matrices, in automatic speech recognition

机译:一种自动语音识别中通过变换矩阵进行噪声自适应的方法

摘要

The improved noise adaptation technique employs a linear or non-linear transformation to the set of Jacobian matrices corresponding to an initial noise condition. An &agr;-adaptation parameter or artificial intelligence operation is employed in a linear or non-linear way to increase the adaptation bias added to the speech models. This corrects shortcomings of conventional Jacobian adaptation, which tend to underestimate the effect of noise. The improved adaptation technique is further enhanced by a reduced dimensionality, principal component analysis technique that reduces the computational burden, making the adaptation technique beneficial in embedded recognition systems.
机译:改进的噪声适应技术对对应于初始噪声条件的雅可比矩阵集采用线性或非线性变换。以线性或非线性方式采用自适应参数或人工智能操作,以增加添加到语音模型的自适应偏差。这纠正了传统雅可比适应性的缺点,这些缺点往往会低估噪声的影响。改进的自适应技术通过减少维数,减少计算负担的主成分分析技术而得到进一步增强,从而使自适应技术在嵌入式识别系统中受益。

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