INTRODUCTION

CN-Celeb, a large-scale speaker recognition dataset collected 'in the wild'.
The dataset contains more than 130,000 utterances from 1,000 Chinese celebrities, and covers 11 different genres in real world.
All the audio files are coded as singlechannel and sampled at 16kHz with 16-bit precision.

The data collection process was organized by the Center for Speech and Language Technologies, Tsinghua University.
It was also funded by the National Natural Science Foundation of China No. 61633013, and the Postdoctoral Science Foundation of China No. 2018M640133.

LOCAL DOWNLOAD (not recommended)

The data can be download from our local server at CSLT@Tsinghua.
  • wav.tgz : speech data[30GB] (download from openslr please)
  • info.txt : info
  • about.html : about
  • index.html : this file
  • The above links are from our own web server at Tsinghua University, which may be not stable and slow for some connections.

    PUBLIC DOWNLOAD (recommended)

    The mirrors in the public OpenSLR cloud can be used as:
  • OpenSLR: http://www.openslr.org/82/
  • LICENSE

    All the resources contained in the database are free for research institutes and individuals.
    No commerical usage is permitted.

    We are very happy if you cite the following paper in your publications:
    @misc{fan2019cnceleb,
      title={CN-CELEB: a challenging Chinese speaker recognition dataset},
      author={Yue Fan and Jiawen Kang and Lantian Li and Kaicheng Li and Haolin Chen and Sitong Cheng and Pengyuan Zhang and Ziya Zhou and Yunqi Cai and Dong Wang},
      year={2019},
      eprint={1911.01799},
      archivePrefix={arXiv},
      primaryClass={eess.AS}
    }
    

    PEOPLE

    Dong Wang, Yue Fan, Jiawen Kang, Lantian Li, Kaicheng Li, Haolin Chen, Sitong Cheng, Pengyuan Zhang, Ziya Zhou, Yunqi Cai

    CONTACTOR

  • Dong Wang: wangdong99@mails.tsinghua.edu.cn
  • Lantian Li: lilt@cslt.org
  • Yue Fan: fanyue@cslt.org
  • Jiawen Kang: kangjw@cslt.org

  • Address: ROOM 1-303, BLDG FIT, CSLT, Tsinghua University
  • Homepage: http://cslt.org or http://cslt.riit.tsinghua.edu.cn
  • ChangeLOG

    2019/11/07: First release