Synchronization rules for HMM-based audio-visual laughter synthesis

Autor:	Jérôme Urbain, Thierry Dutoit, Huseyin Cakmak
Rok vydání:	2015
Předmět:	Constraint (information theory) Laughter Transcription (linguistics) Computer science ComputerApplications_MISCELLANEOUS Mean opinion score Speech recognition media_common.quotation_subject Synchronization (computer science) Audio visual Hidden Markov model media_common
Zdroj:	ICASSP
DOI:	10.1109/icassp.2015.7178382
Popis:	In this paper we propose synchronization rules between acoustic and visual laughter synthesis systems. This work follows up our previous studies on acoustics laughter synthesis and visual laughter synthesis. The need of synchronization rules comes from the constraint that in laughter, HMM-based synthesis of laughter cannot be performed using a unified system where common transcriptions may be used. Therefore acoustic and visual models are trained independently without any synchronization constraints. In this work, we propose simple rules derived from the analysis of audio and visual laughter transcriptions in order to generate visual laughter transcriptions starting from acoustic transcriptions. A perceptive Mean Opinion Score (MOS) test is conducted to evaluate the method.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::21a3bb7af09cefd766705107ddee588d https://doi.org/10.1109/icassp.2015.7178382 Zobrazit plný text záznamu