MSceneSpeech: A Multi-Scene Speech Dataset For Expressive Speech Synthesis
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arXiv
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| Autori principali: | , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866917727761858560 |
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| author | Yang, Qian Zuo, Jialong Su, Zhe Jiang, Ziyue Li, Mingze Zhao, Zhou Chen, Feiyang Wang, Zhefeng Huai, Baoxing |
| author_facet | Yang, Qian Zuo, Jialong Su, Zhe Jiang, Ziyue Li, Mingze Zhao, Zhou Chen, Feiyang Wang, Zhefeng Huai, Baoxing |
| contents | We introduce an open source high-quality Mandarin TTS dataset MSceneSpeech (Multiple Scene Speech Dataset), which is intended to provide resources for expressive speech synthesis. MSceneSpeech comprises numerous audio recordings and texts performed and recorded according to daily life scenarios. Each scenario includes multiple speakers and a diverse range of prosodic styles, making it suitable for speech synthesis that entails multi-speaker style and prosody modeling. We have established a robust baseline, through the prompting mechanism, that can effectively synthesize speech characterized by both user-specific timbre and scene-specific prosody with arbitrary text input. The open source MSceneSpeech Dataset and audio samples of our baseline are available at https://speechai-demo.github.io/MSceneSpeech/. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_14006 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | MSceneSpeech: A Multi-Scene Speech Dataset For Expressive Speech Synthesis Yang, Qian Zuo, Jialong Su, Zhe Jiang, Ziyue Li, Mingze Zhao, Zhou Chen, Feiyang Wang, Zhefeng Huai, Baoxing Audio and Speech Processing Sound We introduce an open source high-quality Mandarin TTS dataset MSceneSpeech (Multiple Scene Speech Dataset), which is intended to provide resources for expressive speech synthesis. MSceneSpeech comprises numerous audio recordings and texts performed and recorded according to daily life scenarios. Each scenario includes multiple speakers and a diverse range of prosodic styles, making it suitable for speech synthesis that entails multi-speaker style and prosody modeling. We have established a robust baseline, through the prompting mechanism, that can effectively synthesize speech characterized by both user-specific timbre and scene-specific prosody with arbitrary text input. The open source MSceneSpeech Dataset and audio samples of our baseline are available at https://speechai-demo.github.io/MSceneSpeech/. |
| title | MSceneSpeech: A Multi-Scene Speech Dataset For Expressive Speech Synthesis |
| topic | Audio and Speech Processing Sound |
| url | https://arxiv.org/abs/2407.14006 |