Facial expression as an input annotation modality for affective speech-to-speech translation
2012 (English)Conference paper (Refereed)Text
One of the challenges of speech-to-speech translation is to accurately preserve the paralinguistic information in the speaker’s message. In this work we explore the use of automatic facial expression analysis as an input annotation modality to transfer paralinguistic information at a symbolic level from input to output in speech-to-speech translation. To evaluate the feasibility of this ap- proach, a prototype system, FEAST (Facial Expression-based Affective Speech Translation) has been developed. FEAST classifies the emotional state of the user and uses it to render the translated output in an appropriate voice style, using expressive speech synthesis.
Place, publisher, year, edition, pages
Engineering and Technology
IdentifiersURN: urn:nbn:se:kth:diva-185527OAI: oai:DiVA.org:kth-185527DiVA: diva2:922771
Workshop on Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction
QC 201604262016-04-252016-04-212016-06-02Bibliographically approved