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Protein Mechanics: from Single Molecule Force Spectroscopy toProtein-based Bi...
化工系膜中心学术论坛-MOF Chemistry: From design strategies to Applications
清华大学材料科学与工程研究院《材料科学论坛》学术报告:Multi-aspect characteri...
Brain-like spiking neural networks: A 4th generation of neural network models
报告题目:
The I2R-NTU submission for NIST RT-07 Conference Room Recording Speaker Diarization
 报告人:
Dr. Chng Eng Siong
Nanyang Technological University
报告时间:
2007-06-27 15:00
报告地点:
Room 3-125, FIT building
主办单位:
信研院
  简介:

Biography
Chng Eng Siong graduated with a BEng (Hons) degree and a PhD degree from Department of Electrical and Electronics Engineering, University of Edinburgh in 1991 and 1996 respectively. After graduating, Dr Chng worked briefly in RIKEN (http://www.brain.riken.jp/ Japan) as a post-doctoral research staff before joining Institute of System Science (ISS) (Singapore) from 1996-1999.  In ISS, he was active in the area of online handwriting recognition and speech recognition systems with the Apple-ISS team.  He subsequently joined Lernout and Hauspie (1999-2001) and continued working in speech research. From 2001-2002, he joined Knowles Electronics (www.knowles.com) as Research Manager for microphone array. He joined Nanyang Technological University as assistant professor in 2003. He is currently supervising five PhD students and one MEng student working in speech and video processing related activities. His interests are: pattern recognition, DSP, speech enhancement and speech processing.

Abstract
This talk describes the I2R/NTU system submitted for the NIST Rich Transcription 2007 (RT-07) Meeting Recognition evaluation Multiple Distant Microphone (MDM) task. In our system, speaker turn detection and clustering is done using Direction of Arrival (DOA) in-formation. Purification of the resultant speaker clusters is then done by performing GMM modeling on acoustic features. As a final step, non- speech & silence removal is done. Our system achieved a competitive overall DER of 15.32% for the NIST Rich Transcription 2007 evaluation task.

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