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We propose a method for speech-to-speech emotionpreserving translation thatoperates at the level of discrete speech units. Our approach relies on the useof multilingual emotion embedding that can capture affective information in alanguage-independent manner. We show that this embedding can be used to predictthe pitch and duration of speech units in a target language, allowing us toresynthesize the source speech signal with the same emotional content. Weevaluate our approach to English and French speech signals and show that itoutperforms a baseline method that does not use emotional information,including when the emotion embedding is extracted from a different language.Even if this preliminary study does not address directly the machinetranslation issue, our results demonstrate the effectiveness of our approachfor cross-lingual emotion preservation in the context of speech resynthesis.

Learning Multilingual Expressive Speech Representation for Prosody Prediction without Parallel Data