Presentation 2011-10-06
Analysis of laughter annotation : towards support for children with autistic spectrum disorders
Hiroki Tanaka, Hideki Kashioka, Nick Campbell,
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Abstract(in English) People on the autistic dimension often have great difficulty in understanding human engagement underlying paralinguistic signals and laughter. Our current work focusses on detecting different types of laughter to measure engagement. This report presents the results of a preliminary analysis of the sounds of laughs in a very large corpus of naturally-occurring conversational speech. Four types of laughter were categorized, and our goal is to enable children with autistic spectrum to classify these laughs. A teacher who specialises in Social Skill Training for children with autistic spectrum annotated these types of laughter manually, based on listening. We analyzed acoustic features of this annotation result, and greater than 58% classification accuracy was achieved by SVM statistical methods.
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Keyword(in English) Autistic Spectrum / Laughter / Paralinguistics / Nonlinguistic
Paper # SP2011-60,WIT2011-42
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Committee WIT
Conference Date 2011/9/29(1days)
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Registration To Well-being Information Technology(WIT)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Analysis of laughter annotation : towards support for children with autistic spectrum disorders
Sub Title (in English)
Keyword(1) Autistic Spectrum
Keyword(2) Laughter
Keyword(3) Paralinguistics
Keyword(4) Nonlinguistic
1st Author's Name Hiroki Tanaka
1st Author's Affiliation Nara Institute of Science and Technology()
2nd Author's Name Hideki Kashioka
2nd Author's Affiliation Nara Institute of Science and Technology:National Institute of Information and Communications Technology
3rd Author's Name Nick Campbell
3rd Author's Affiliation Nara Institute of Science and Technology:Trinity College Dublin
Date 2011-10-06
Paper # SP2011-60,WIT2011-42
Volume (vol) vol.111
Number (no) 226
Page pp.pp.-
#Pages 6
Date of Issue