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System and method for neural network based feature extraction for acoustic model development

机译:用于声学模型开发的基于神经网络的特征提取系统和方法

摘要

A system and method are presented for neural network based feature extraction for acoustic model development. A neural network may be used to extract acoustic features from raw MFCCs or the spectrum, which are then used for training acoustic models for speech recognition systems. Feature extraction may be performed by optimizing a cost function used in linear discriminant analysis. General non-linear functions generated by the neural network are used for feature extraction. The transformation may be performed using a cost function from linear discriminant analysis methods which perform linear operations on the MFCCs and generate lower dimensional features for speech recognition. The extracted acoustic features may then be used for training acoustic models for speech recognition systems.
机译:提出了一种用于基于神经网络的特征提取以进行声学模型开发的系统和方法。神经网络可用于从原始MFCC或频谱中提取声学特征,然后将其用于训练语音识别系统的声学模型。可以通过优化线性判别分析中使用的成本函数来执行特征提取。由神经网络生成的一般非线性函数用于特征提取。可以使用来自线性判别分析方法的成本函数执行变换,该线性判别分析方法对MFCC执行线性运算并生成用于语音识别的较低维特征。然后,所提取的声学特征可以用于训练语音识别系统的声学模型。

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