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Feature extraction of modulation for automatic speech recognition

机译:用于自动语音识别的调制特征提取

摘要

An automatic speech recognition apparatus and method with a front end feature extractor that improves recognition performance under adverse acoustic conditions are disclosed. The inventive feature extractor is characterized by a critical bandwith spectral resolution, an emphasis on slow changes in the spectral structure of the speech signal, and adaptive automatic gain control. The feature extractor includes a feature generator (30) configured to compute short-term parameters of the speech signal, a filter system (32) configured to filter the time sequences of the short-term parameters, and a normalizer (34) configured to normalize the filtered parameters with respect to one or more previous values of the filtered parameters. Accordingly, the feature extractor is operable to carry out the following steps: computing short-term parameters of the speech signal; filtering time sequences of the short-term parameters; and normalizing the filtered parameters with respect to one or more previous values of the filtered parameters. The steps of filtering and normalizing preferably are performed independently of one another.
机译:公开了一种具有前端特征提取器的自动语音识别设备和方法,其在不利的声学条件下提高了识别性能。本发明的特征提取器的特征在于具有频谱分辨率的临界频带,强调语音信号的频谱结构的缓慢变化以及自适应自动增益控制。特征提取器包括被配置为计算语音信号的短期参数的特征发生器(30),被配置为对短期参数的时间序列进行滤波的滤波器系统(32)以及被配置为进行归一化的归一化器(34)。相对于已过滤参数的一个或多个先前值的已过滤参数。因此,特征提取器可操作以执行以下步骤:计算语音信号的短期参数;以及过滤短期参数的时间序列;相对于过滤后的参数的一个或多个先前值归一化过滤后的参数。滤波和归一化的步骤优选地彼此独立地执行。

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