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QI-TTS: Questioning Intonation Control for Emotional Speech Synthesis

Haobin Tang, Xulong Zhang, Jianzong Wang, Ning Cheng, Jing Jian Xiao

202313 citationsDOI

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.

Topics & Concepts

Intonation (linguistics)Computer scienceSyllableSentenceSpeech synthesisSpeech recognitionFocus (optics)Style (visual arts)Control (management)UtteranceNatural language processingLinguisticsArtificial intelligenceOpticsPhysicsArchaeologyPhilosophyHistorySpeech Recognition and SynthesisPhonetics and Phonology ResearchTopic Modeling
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