from    
to    
search  

 


Photoexcitation of Complex Molecular Systems through Combined FirstPrinciples...
全球变化科学紫荆论坛第439期:基于850hPa相对涡度的热带气旋路径追踪识别方法
Controlling the Structure of Inference and Learning in Neural Networks
环境学术沙龙第698期:城市水系统综合管理:关键铁盐化学品的生产与利用
报告题目:
Emotional Speech: Its Production and Recognition
 报告人:
Sungbok Lee
University of Southern California
报告时间:
2007-07-11 14:30
报告地点:
Room 1-315, FIT building, Tsinghua University
主办单位:
信研院语音和语言技术研究中心
  简介:

Biography :

Professor Sungbok Lee was born in Korea in 1954. He received Ph. D degree in Biomedical Engineering from the University of Alabama at Birmingham in 1991. He worked as a research engineer for the Central Institute for the Deaf at Washington University during 1991 - 1997, and as a research consultant at AT&T and Lucent Bell Labs during 1998 - 2002. Now he is a research professor at University of Southern California. His main research interests are in speech production, speech signal processing and recognition including emotional speech.

Abstract:

While acoustic characteristics of emotional speech have been well documented in the literature, much less knowledge is available in the articulatory domain. Recently we have collected vocal tract data, simultaneously with speech recordings, using an electromagnetic articulograph (EMA) and a fast magnetic resonance imaging (MRI) technique while subjects produce utterances in four different acted emotions (anger, sadness, happiness and neutral). The data have been analyzed in terms of the kinematics of the tongue tip and jaw movements as a function of emotion. Articulatory timing as well as difference in the vocal tract shaping are also investigated using the functional data analysis (FDA) techniques. It is confirmed that emotion affects the tongue tip positioning and jaw opening. Furthermore the tongue tip movement range and velocity vary significantly from emotion to emotion, which implies that spectral contrasts exist among the emotions. In summary, speakers encode emotional change by modifying the place and manner of articulation while preserving linguistic identities of words. Accordingly, it is hypothesized that a robust acoustic model set trained with neutral or normal speech be effective for discriminating emotional categories. The hypothesis is tested with neutral speech HMMs trained with the TIMIT database and tested with two emotional speech databases: one is microphone and the other telephone speech. About 65% and 63% of discrimination accuracies are achieved, respectively, which supports the hypothesis. Interestingly, the plain mel-filterbank output features outperformed the mel-frequencies cepstral coefficients in that task. Detailed procedures and results will be presented and discussed.

今日相关信息
 
同类别相关信息
清华信息大讲堂179讲:Radio Access Ne...
清华信息大讲堂178讲:用于人类决策的...
Efficient and Effective Models for ...
设计研究:前沿进展”学术研讨会 Desi...
Building Generalizable Agents by Le...
学术活动