Chinese Dialect Identification Based on Gender Classification

摘要：

This paper designs a novel Chinese dialect identification system based on gender classification. RelAtive SpecTrAl Perceptual Linear Predictive (RASTA-PLP) coefficients are applied to construct gender dependent GMM models. Gender classification is conducted before testing. The gender classification criterion is the average pitch of the segment of testing speech. Experiments are evaluated on Chinese dialect telephone speech corpus which was recorded by our laboratory. The results demonstrate significant improvement in Chinese dialect identification compare to the gender independent method with a slight increase in the processing computation. The improved performance can attain 3.77％ at least.

关键词： Dialect identification Pitch RASTA-PLP GMM

作者: Wang Xia Gu Mingliang Gao Yuan Ma Yong

作者单位: School of Physics and Electronic EngineeringXuzhou Normal UniversityXuzhou, China School of Linguistic Science Xuzhou Normal UniversityXuzhou, China School of Physics and Electronic Engineering Xuzhou Normal University Xuzhou, China

会议类型: 国际会议

会议名称: 2011年无线通信与信号处理国际会议(WCSP 2011)

会议地点: 南京

会议语种:英文

页码: 1-5

在线出版日期: 2011-11-09（万方平台首次上网日期，不代表论文的发表时间）