Title :
Annotating conversational speech for corpus-based dialogue speech synthesizer — A first step
Author :
Mori, Hisamichi ; Hitomi, Tadaaki
Author_Institution :
Grad. Sch. of Eng., Utsunomiya Univ., Utsunomiya, Japan
Abstract :
This paper describes an HMM-based speech synthesis that allows dimensional description of emotion as inputs. A spontaneous dialogue speech corpus that was designed for studying paralinguistic phenomena in expressive social interactions was used to train the models, utilizing its emotional state description as additional contextual factors. In the perceptual experiment, a very high correlation was observed (R ≃ 0.8) between given pleasantness/arousal values and averaged subjective evaluations, which means that the synthesized utterances could successfully convey specified paralinguistic information.
Keywords :
audio databases; hidden Markov models; linguistics; speech synthesis; HMM-based speech synthesis; arousal value; conversational speech annotation; corpus-based dialogue speech synthesizer; emotion dimensional description; emotional state description; expressive social interaction; hidden Markov model; paralinguistic information; paralinguistic phenomenon; pleasantness value; spontaneous dialogue speech corpus; subjective evaluation; Context; Correlation; Databases; Hidden Markov models; Pragmatics; Speech; Speech synthesis; HMM-based speech synthesis; UU Database; spontaneous speech;
Conference_Titel :
Speech Database and Assessments (Oriental COCOSDA), 2012 International Conference on
Conference_Location :
Macau
Print_ISBN :
978-1-4673-2811-1
Electronic_ISBN :
978-1-4673-2812-8
DOI :
10.1109/ICSDA.2012.6422461
