DFKI-LT - Facial expression as an input annotation modality for affective speech-to-speech translation
Facial expression as an input annotation modality for affective speech-to-speech translation
1 International Workshop on Multimodal Analyses for Human Machine Interaction (MA3), Santa Cruz, CA, USA, Online, 9/2012
One of the challenges of speech-to-speech translation is to accurately preserve the paralinguistic information in the speakers 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 approach, 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.
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