Emilia: An Extensive, Multilingual, and Diverse Speech Dataset for Large-Scale Speech Generation

• URL: http://arxiv.org/abs/2407.05361v3
• Date: Sat, 7 Sep 2024 15:08:24 GMT
• Title: Emilia: An Extensive, Multilingual, and Diverse Speech Dataset for Large-Scale Speech Generation
• Authors: Haorui He, Zengqiang Shang, Chaoren Wang, Xuyuan Li, Yicheng Gu, Hua Hua, Liwei Liu, Chen Yang, Jiaqi Li, Peiyang Shi, Yuancheng Wang, Kai Chen, Pengyuan Zhang, Zhizheng Wu,
• Abstract summary: Emilia is the first large-scale, multilingual, and diverse speech generation dataset. It starts with over 101k hours of speech across six languages, covering a wide range of speaking styles. To facilitate the scale-up of Emilia, we also present Emilia-Pipe, the first open-source preprocessing pipeline.
• Score: 26.569097905515033
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Recent advancements in speech generation models have been significantly driven by the use of large-scale training data. However, producing highly spontaneous, human-like speech remains a challenge due to the scarcity of large, diverse, and spontaneous speech datasets. In response, we introduce Emilia, the first large-scale, multilingual, and diverse speech generation dataset. Emilia starts with over 101k hours of speech across six languages, covering a wide range of speaking styles to enable more natural and spontaneous speech generation. To facilitate the scale-up of Emilia, we also present Emilia-Pipe, the first open-source preprocessing pipeline designed to efficiently transform raw, in-the-wild speech data into high-quality training data with speech annotations. Experimental results demonstrate the effectiveness of both Emilia and Emilia-Pipe. Demos are available at: https://emilia-dataset.github.io/Emilia-Demo-Page/.

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