QI-TTS: Questioning Intonation Control for Emotional Speech Synthesis
Haobin Tang, Xulong Zhang, Jianzong Wang, Ning Cheng, Jing Xiao
Abstract
Recent expressive text to speech (TTS) models focus on synthesizing emotional speech, but some fine-grained styles such as intonation are neglected. In this paper, we propose QI-TTS which aims to better transfer and control intonation to further deliver the speaker’s questioning intention while transferring emotion from reference speech. We propose a multi-style extractor to extract style embedding from two different levels. While the sentence level represents emotion, the final syllable level represents intonation. For fine-grained intonation control, we use relative attributes to represent intonation intensity at the syllable level. Experiments have validated the effectiveness of QI-TTS for improving intonation expressiveness in emotional speech synthesis.
BibTeX
@inproceedings{icassp2023_qittsquestioning,
title = {QI-TTS: Questioning Intonation Control for Emotional Speech Synthesis},
author = {Haobin Tang and Xulong Zhang and Jianzong Wang and Ning Cheng and Jing Xiao},
booktitle = {ICASSP 2023},
year = {2023}
}