A PRIVACY-PRESERVING AND LANGUAGE-INDEPENDENT SPEECH PROCESSING AND CHARACTERISTICS MEASURING METHOD FOR SPONTANEOUS CONVERSATION

被引：0

作者：

Zhang, Ni ^{[1
]}

机构：

[1] Fujitsu Labs Ltd, Human Ctr Comp Lab, Kawasaki, Kanagawa 211, Japan

来源：

4TH INTERNATIONAL CONFERENCE ON SOFTWARE TECHNOLOGY AND ENGINEERING (ICSTE 2012) | 2012年

关键词：

Speech processing; Prosodic features; Voiced/unvoiced sound; Hidden Markov Model; CLASSIFICATION;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Conversation conveys important social signals of human interaction that indicates interest, service-awareness, persuasiveness, etc. Our research aims at perceiving human interest and intention by identifying social signals of interaction in their conversation. In this paper, the author introduces a privacy-preserving and language-independent speech processing approach to measure vocal interaction characteristics for spontaneous conversation in-between two people. The approach has been tested with Japanese, English, and Chinese so far. The experimental results prove that it is possible to identify the difference of speaking styles and interaction pattern using the conversation characteristics measured.

引用

页码：19 / 25

页数：7

共 13 条

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