计算机工程与应用2011，Vol.47Issue(11)：114-117,4.DOI:10.3778/j.issn.1002-8331.2011.11.033
基于GMM的说话人识别技术研究
Research on GMM based speaker recognition technology
摘要
Abstract
In order to investigate the function of Ganssian Mixture Model(GMM) in speaker recognition, a GMM based speaker recognition system is designed.The system consists of four modules that are audio signal pre-processing, speech activity detection,speaker modeling as well as audio signal recognition. The first three modules constitute the model training segment of the system and the last module constitutes the speech recognition segment of the system.A speech activity detector which is built by GMM in the second module is the innovation of the research. Some tunable parameters and recognition error rate of the system are tested using audio-visual meetings in the Augmented Multi-party Interaction(AMI) corpus. Simulations show that with the help of the speech activity detector and several filter algorithms,recognition accuracy rate of the system for audio signal with overlap speech can reach 83.02％.关键词
高斯混合模型/语音活动检测/识别错误率Key words
Gaussian Mixture Model(GMM)/ speech activity detection /recognition error rate分类
信息技术与安全科学引用本文复制引用
曹洁,潘鹏..基于GMM的说话人识别技术研究[J].计算机工程与应用,2011,47(11):114-117,4.基金项目
甘肃省自然科学基金(the Natural Science Foundation of Gansu Province of China under Grant No.1010RJZA046) （the Natural Science Foundation of Gansu Province of China under Grant No.1010RJZA046）
甘肃省教育厅研究生导师基金项目(No.0914ZTB003). （No.0914ZTB003）
