A improved speech synthesis system utilizing BPSO-based lip feature selection

Author

Wang, Mengjun ; Wang, Xiangling ; Li, Gang

Author_Institution

Sch. of Inf. Eng., HeBei Univ. of Technol., Tianjin, China

Volume

3

fYear

2011

fDate

15-17 Oct. 2011

Firstpage

1292

Lastpage

1295

Abstract

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%.

Keywords

Gaussian processes; biomedical optical imaging; feature extraction; hidden Markov models; image recognition; medical image processing; particle swarm optimisation; speech; speech recognition; Gaussian mixture component; HMM; binary particle swarm optimization algorithm; hidden Markov models; integrated discriminate vector; lip feature selection; lipreading recognition; pixel based feature; recognition rates; speaker dependent case; speech synthesis system; visual speech; Discrete cosine transforms; Feature extraction; Hidden Markov models; Image sequences; Speech; Vectors; Visualization; Binary Particle Swarm Optimization; Hidden Markov Model; feature Selection; normalized DCT coefficients; normalized geometrical feature;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Informatics (BMEI), 2011 4th International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-9351-7

Type

conf

DOI

10.1109/BMEI.2011.6098551

Filename

6098551