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Real time speech / speaker recognition by using digital cochlea system

使用数字耳蜗系统进行实时语音/说话人识别

基本信息

批准号：
12650397
负责人：
HANGAI Seiichiro
金额：
$ 2.05万
依托单位：
Tokyo University of Science
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2000
资助国家：
日本
起止时间：
2000 至 2001
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-12650397/
关键词：
Digital cochlea Speech recognition Speaker recognition DSP Real time processing Speech processing ディジタル蝸牛

项目摘要

In this research, we discuss the speech/speaker recognition system using Digital Cochlear Model as follows.1. Optimization of Digital Cochlear ModelWe optimize the Digital Cochlear Model for installation on DSP. It has 16 section consists of traveling-wave filter, velocity transformation filter and second filter.2. Investigation of speech/speaker recognition algorithm for Digital CochleaWe propose the Dynamic Time Warping algorithm and the enhancement of difference between adjacent outputs of Digital Cochlea. They can improve the recognition performance and the robustness against noise.3. Realization of Digital Cochlea filterWe design the digital cochlea on 32 DSP boards. TMS320C3xDSK. Real-time speech processing can be done by this Digital Cochlear filter.4. Application to real-time speech recognitionWe examine the real-time speech recognition using this system under various noisy environment. From experimental results, we achieve 99.2% recognition rate under silent environment. 90.6% under 10dB SXR and 41.0% under 5dB SXR.5. Application to real-time speaker recognitionWe examine the real-time speaker recognition for 18 persons using this system. We achieve 92.2% speaker recognition rate. In addition, we achieve 98.9% by adjusting the gain of each section of Digital Cochlear filter.

在本研究中，我们讨论了使用数字耳蜗模型的语音/说话人识别系统如下： 1．数字耳蜗模型的优化我们优化了数字耳蜗模型以安装在 DSP 上。它有16段，由行波滤波器、速度变换滤波器和二次滤波器组成。 2．数字耳蜗语音/说话人识别算法的研究我们提出了动态时间规整算法和数字耳蜗相邻输出之间差异的增强。它们可以提高识别性能和抗噪声的鲁棒性。 3．数字耳蜗滤波器的实现我们在32块DSP板上设计了数字耳蜗。 TMS320C3xDSK。数字耳蜗滤波器可以实现实时语音处理。4．实时语音识别的应用我们在各种噪声环境下使用该系统检查实时语音识别。从实验结果来看，我们在安静环境下的识别率达到了99.2%。 10dB SXR 下为 90.6%，5dB SXR 下为 41.0%。5。实时说话人识别的应用我们使用该系统检查 18 个人的实时说话人识别情况。我们实现了 92.2% 的说话人识别率。另外，我们通过调整数字耳蜗滤波器各部分的增益，达到了98.9%。