Speech Recognition System Based on Integrating feature and HMM

摘要：

Automatic speech processing systems are employed more and more often in real environments. However, they are confronted with high ambient noise levels and their performance degrades drastically. A robust and practical speech recognition system using integrating feature and Hidden Markov Model (HMM) was proposed aiming at improving speech recognition rate in noise environmental conditions. It integrated different speech features into the system, based on global optimization, a new Genetic Algorithm (GA) for training HMM was proposed. The system is comprised of three main sections, a pre-processing section, a feature extracting section and a HMM processing section. Six Chinese vowels were taken as the experimental data. Recognition experiments show that the method is effective and high speed and accuracy for speech recognition.

关键词： speech recognition integrating feature hidden markov mode(HMM) genetic algorithm(GA)

作者: Zhao Lishuang Han Zhiyan

作者单位: Bohai University of Information Science & Engineering, Jinzhou, Liaoning, 121000, China

会议类型: 国际会议

会议名称: 2010 International Conference on Measuring Technology and Mechatronics Automation(ICMTMA 2010)(2010年检测技术与机电自动化国际会议)

会议地点: 长沙

会议语种:英文

页码: 2703-2706

在线出版日期: 2010-03-13（万方平台首次上网日期，不代表论文的发表时间）