SEQUENCE-TO-SEQUENCE MODELLING OF F0 FOR SPEECH EMOTION CONVERSION - Sorbonne Université Access content directly
Conference Papers Year : 2019

SEQUENCE-TO-SEQUENCE MODELLING OF F0 FOR SPEECH EMOTION CONVERSION

Abstract

Voice interfaces are becoming wildly popular and driving demand for more advanced speech synthesis and voice transformation systems. Current text-to-speech methods produce realistic sounding voices, but they lack the emotional expressivity that listeners expect , given the context of the interaction and the phrase being spoken. Emotional voice conversion is a research domain concerned with generating expressive speech from neutral synthesised speech or natural human voice. This research investigated the effectiveness of using a sequence-to-sequence (seq2seq) encoder-decoder based model to transform the intonation of a human voice from neutral to expressive speech, with some preliminary introduction of linguistic conditioning. A subjective experiment conducted on the task of speech emotion recognition by listeners successfully demonstrated the effectiveness of the proposed sequence-to-sequence models to produce convincing voice emotion transformations. In particular, conditioning the model on the position of the syllable in the phrase significantly improved recognition rates.
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Dates and versions

hal-02018439 , version 1 (13-02-2019)

Identifiers

  • HAL Id : hal-02018439 , version 1

Cite

Carl Robinson, Nicolas Obin, Axel Roebel. SEQUENCE-TO-SEQUENCE MODELLING OF F0 FOR SPEECH EMOTION CONVERSION. IEEE International Conference on Acoustics, Speech, and Signal Processing, May 2019, Brighton, United Kingdom. ⟨hal-02018439⟩
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