Summary of Towards Controllable Speech Synthesis in the Era Of Large Language Models: a Survey, by Tianxin Xie et al.
Towards Controllable Speech Synthesis in the Era of Large Language Models: A Survey
by Tianxin Xie, Yan Rong, Pengfei Zhang, Li Liu
First submitted to arxiv on: 9 Dec 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG); Multimedia (cs.MM); Sound (cs.SD); Audio and Speech Processing (eess.AS)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a comprehensive survey of controllable text-to-speech (TTS) technologies, which have evolved beyond generating human-like speech to enable fine-grained control over various attributes such as emotion, prosody, timbre, and duration. The authors examine the general pipeline, challenges, model architectures, and control strategies used in controllable TTS, providing a taxonomy of existing methods. They also summarize datasets and evaluation metrics, highlighting applications and future directions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Controllable text-to-speech (TTS) lets computers create speech that sounds natural and can even be controlled to have certain emotions or tones. Researchers are working on making this technology better by giving it more control over the way the speech sounds. This paper looks at all the different ways people are trying to make controllable TTS work, from basic techniques to using big language models. It also talks about the challenges and problems that need to be solved to make it happen. |
