第22回 ロボット聴覚特集 - 奥乃研究室 - 京都大学

社 団 法 人 人 工 知 能 学 会Japanese Society forArtificial Intelligence人 工 知 能 学 会JSAI Technical ReportSIG-CHallege-0522-12 (10/15)Using prosodic and voice quality features for paralinguistic information extraction in dialog speech * Carlos Toshinori ISHI, Hiroshi ISHIGURO, Norihiro HAGITA (ATR Intelligent Robotics andCommunication Laboratories)carlos@atr.jpishiguro@ams.eng.osaka-u.ac.jp hagita@atr.jpAbstract - The use of voice quality features in additionto classical prosodic features is proposed for automaticextraction of paralinguistic information (like speech acts,attitudes and emotions) in dialog speech. Perceptualexperiments and acoustic analysis are conducted formonosyllabic utterances spoken in several speakingstyles, carrying a variety of paralinguistic information.Acoustic parameters related with prosodic and voicequality features potentially representing the variations inspeaking styles are evaluated. Experimental resultsindicate that prosodic features are effective foridentifying some groups of speech acts with specificfunctions, while voice quality features are useful foridentifying utterances with an emotional or attitudinalexpressivity.1 phonation style[6] modal ( ), breathy whispery ( ), vocal fry creaky (), harsh ventricular(), pressed () [6][7,8,9,10]1 F0 contourTonePhonetic& durationpattern [7]informationVocal FryVocal FrySpeechdetection [8]RatesignalParalinguisticAperiodicityAperiodicityinformationdetection [9] Rateextractionspeech actAspir. noiseAsp. Noiseattitudedetection [10]RateemotionFrame level orUtterancesegment levellevelFig. 1 Block diagram of the proposed framework forF0 paralinguistic information extraction.(prosodic features)2 [1,2,3,4](expressive 2.1 speech) non-modal F0 [5]1 Phonetic information “voice quality”ProsodyVoice quality71