基于二阶差分耳蜗模型的语音识别新方法

A New Approach of Speech Recognition Based on Second-Order Difference Cochlear Model

采用二阶差分耳蜗模型对语音信号进行特征参数提取 ,获得了基于听觉谱的语音识别前端特征参数 ,同时根据听觉谱特征提出了一种“幅和频差积”距离测度 ,识别算法采用端点放松两帧 ,路径斜率限制在 1/ 2到 2之间的改进型 DTW算法 .在小词汇量非特定人 (SI)的识别环境下 ,计算机模拟结果表明此法在对 0～ 9十个数字以及小词汇量的 SI识别时 ,其正识率可达 98%以上 。

In this paper, the second order difference cochlear model is used to extract the speech parameters. A kind of speech recognition front end parameters based on auditory spectrum is obtained. A new “amplitude sum multiplied by frequency difference” distance measure is proposed according to the feature of speech parameters. The recognition algorithm is an improved DTW algorithm that sets two free frames in the beginning of speech segments and has the trace slope between 1/2 and 2. Under the recognition condition of small vocabulary or digits vocabulary and speaker independence, computer simulation shows that the algorithm attains an recognition accuracy of at least 98 percent, and it has the quite good robustness as well.