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Vocal tract shaping of emotional speech.
Kim, Jangwon; Toutios, Asterios; Lee, Sungbok; Narayanan, Shrikanth S.
Afiliación
  • Kim J; Signal Analysis and Interpretation Laboratory University of Southern California, Los Angeles, CA, USA.
  • Toutios A; Signal Analysis and Interpretation Laboratory University of Southern California, Los Angeles, CA, USA.
  • Lee S; Signal Analysis and Interpretation Laboratory University of Southern California, Los Angeles, CA, USA.
  • Narayanan SS; Signal Analysis and Interpretation Laboratory University of Southern California, Los Angeles, CA, USA.
Comput Speech Lang ; 642020 Nov.
Article en En | MEDLINE | ID: mdl-32523241
ABSTRACT
Emotional speech production has been previously studied using fleshpoint tracking data in speaker-specific experiment setups. The present study introduces a real-time magnetic resonance imaging database of emotional speech production from 10 speakers and presents articulatory analysis results of speech emotional expression using the database. Midsagittal vocal tract parameters (midsagittal distances and the vocal tract length) were parameterized based on a two-dimensional grid-line system, using image segmentation software. The principal feature analysis technique was applied to the grid-line system in order to find the major movement locations. Results reveal both speaker-dependent and speaker-independent variation patterns. For example, sad speech, a low arousal emotion, tends to show smaller opening for low vowels in the front cavity than the high arousal emotions more consistently than the other regions of the vocal tract. Happiness shows significantly shorter vocal tract length than anger and sadness in most speakers. Further details of speaker-dependent and speaker-independent speech articulation variation in emotional expression and their implications are described.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Comput Speech Lang Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Comput Speech Lang Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos
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