# QI-TTS: Questioning Intonation Control for Emotional Speech Synthesis

arXiv: https://arxiv.org/abs/2303.07682 · HTML: https://mlsanity.com/paper/2303.07682/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 23 references that are in the map.
- First posted on arXiv 14 Mar 2023.

## Builds on (most cited first, 14 of 14)

- [Domain-Adversarial Training of Neural Networks](https://mlsanity.com/paper/1505.07818/) (2015)
- [HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis](https://mlsanity.com/paper/2010.05646/) (2020)
- [FastSpeech 2: Fast and High-Quality End-to-End Text to Speech](https://mlsanity.com/paper/2006.04558/) (2020)
- [Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis](https://mlsanity.com/paper/1803.09017/) (2018)
- [Mockingjay: Unsupervised Speech Representation Learning with Deep Bidirectional Transformer Encoders](https://mlsanity.com/paper/1910.12638/) (2019)
- [Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron](https://mlsanity.com/paper/1803.09047/) (2018)
- [Seen and Unseen emotional style transfer for voice conversion with a new emotional speech dataset](https://mlsanity.com/paper/2010.14794/) (2020)
- [STYLER: Style Factor Modeling with Rapidity and Robustness via Speech Decomposition for Expressive and Controllable Neural Text to Speech](https://mlsanity.com/paper/2103.09474/) (2021)
- [EMOVIE: A Mandarin Emotion Speech Dataset with a Simple Emotional Text-to-Speech Model](https://mlsanity.com/paper/2106.09317/) (2021)
- [Towards Unsupervised Speech Recognition and Synthesis with Quantized Speech Representation Learning](https://mlsanity.com/paper/1910.12729/) (2019)
- [Adversarially learning disentangled speech representations for robust multi-factor voice conversion](https://mlsanity.com/paper/2102.00184/) (2021)
- [Multi-reference Tacotron by Intercross Training for Style Disentangling,Transfer and Control in Speech Synthesis](https://mlsanity.com/paper/1904.02373/) (2019)
- [Into-TTS : Intonation Template Based Prosody Control System](https://mlsanity.com/paper/2204.01271/) (2022)
- [A Study of Modeling Rising Intonation in Cantonese Neural Speech Synthesis](https://mlsanity.com/paper/2208.02189/) (2022)

## Built on by (most cited first, 8 of 8)

- [EmoVoice: LLM-based Emotional Text-To-Speech Model with Freestyle Text Prompting](https://mlsanity.com/paper/2504.12867/) (2025)
- [Laugh Now Cry Later: Controlling Time-Varying Emotional States of Flow-Matching-Based Zero-Shot Text-to-Speech](https://mlsanity.com/paper/2407.12229/) (2024)
- [ED-TTS: Multi-Scale Emotion Modeling using Cross-Domain Emotion Diarization for Emotional Speech Synthesis](https://mlsanity.com/paper/2401.08166/) (2024)
- [Spotlight-TTS: Spotlighting the Style via Voiced-Aware Style Extraction and Style Direction Adjustment for Expressive Text-to-Speech](https://mlsanity.com/paper/2505.20868/) (2025)
- [Voice Conversion with Denoising Diffusion Probabilistic GAN Models](https://mlsanity.com/paper/2308.14319/) (2023)
- [AOSR-Net: All-in-One Sandstorm Removal Network](https://mlsanity.com/paper/2309.08838/) (2023)
- [Enhancing Emotion Recognition in Conversation through Emotional Cross-Modal Fusion and Inter-class Contrastive Learning](https://mlsanity.com/paper/2405.17900/) (2024)
- [Voiced-Aware Style Extraction and Style Direction Adjustment for Expressive Text-to-Speech](https://mlsanity.com/paper/2511.14824/) (2025)

## Abstract (arXiv)

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.