A boosted multi-HMM classifier for recognition of visual speech elements

• المؤلفون الرئيسيون: Foo, Say Wei, Dong, Liang
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2009
• الموضوعات: DRNTU::Engineering::Electrical and electronic engineering
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/90750; http://hdl.handle.net/10220/4590; http://sfxna09.hosted.exlibrisgroup.com:3410/ntu/sfxlcl3?sid=metalib:PUBMED&id=doi:10.1080/02699200400026884&genre=&isbn=&issn=0269-9206&date=&volume=20&issue=2-3&spage=149&epage=56&aulast=Parker&aufirst=%20Mark&auinit=&title=Clin%20Linguist%20Phon&atitle=Automatic%20speech%20recognition%20and%20training%20for%20severely%20dysarthric%20users%20of%20assistive%20technology%3A%20the%20STARDUST%20project%2E
• المؤسسة: Nanyang Technological University

A novel boosted classifier using multiple Hidden Markov Models (HMMs) is reported in this paper. The composite HMMs are specially trained to highlight certain group of training samples with the application of adaptive boosting technique. Experiments were carried out to identify the ba...