节点文献
基于美尔倒谱系数和复杂性的语种辨识
Language Identification Based on MFCC and Complexity
【摘要】 提出一种在传统提取MFCC特征的基础上增加复杂性特征的方法,利用OGI-TS电话语音库对该方法进行性能测试,比较、分析英语、汉语、日语3个语种的识别效果,结果表明,该方法相对于传统方法能明显提高语种识别的准确性和鲁棒性。
【Abstract】 This paper proposes a new method, which uses MFCC combined with complexity. Some experiments are conducted by using OGI-TS telephone speech corpus. Vector quantization method is employed to recognize three languages (English, Mandarin and Japanese), and it analyzes the effects of language identification. It is shown that the method can remarkably improve the recognition accuracy and robustness.
【关键词】 语种辨识;
复杂性;
标准矢量量化;
【Key words】 language identification; complexity; standard vector quantization;
【Key words】 language identification; complexity; standard vector quantization;
【基金】 国家自然科学基金资助项目(60302027)
- 【文献出处】 计算机工程 ,Computer Engineering , 编辑部邮箱 ,2008年19期
- 【分类号】TN912.34
- 【被引频次】3
- 【下载频次】101