A Improved Speech Synthesis System Utilizing BPSO-based Lip Feature Selection

摘要：

To get a higher lipreading recognition result in speech synthesis system driven by visual speech, Binary Particle Swarm Optimization (BPSO) algorithms is used to select the optimal lip feature subset Experiments are carried out based on HMM with 4 states and 16 Gaussian mixture components in a small database for speaker-dependent case. Experiment results show that the integrated discriminate vector after feature selection obtained the information from the geometrical features and the pixel based features. Comparing with feature fusion based on concatenating, the recognition rates with feature selection based on BPSO are improved by as much as 2.42％.

关键词： feature Selection Binary Particle Swarm Optimization normalized geometrical feature normalized DCT coefficients Hidden Markov Model

作者: Mengjun Wang Xiangling Wang Gang Li

作者单位: School of Information Engineering HeBei University of Technology Tianjin, China School of Precision Instrument and Opto-Electronics Engineering, Tianjin University Tianjin, China

会议类型: 国际会议

会议名称: 2011 4th International Conference on Biomedical Engineering and Informatics(第四届生物医学工程与信息学国际会议 BMEI 2011)

会议地点: 上海

会议语种:英文

页码: 1298-1301

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）