CSS10: A Collection of Single Speaker Speech Datasets for 10 Languages

Abstract

We describe our development of CSS10, a collection of single speaker speech datasets for ten languages. It is composed of short audio clips from LibriVox audiobooks and their aligned texts. To validate its quality we train two neural text-to-speech models on each dataset. Subsequently, we conduct Mean Opinion Score tests on the synthesized speech samples. We make our datasets, pretrained models, and test resources publicly available. We hope they will be used for future speech tasks.

For details, check our paper. Kyubyong gave a talk with this paper at the workshop of 2018 The Korean Society of Speech Sciences.

Environments & Dependencies

• Linux
• Python 2.X or 3.X
• TensorFlow == 1.3
• NumPy
• Librosa
• Matplotlib
• tqdm
• scipy

Audiobooks & Datasets

Pretrained Models & Audio Samples

Cite

@article{park2019css10,
  title={CSS10: A Collection of Single Speaker Speech Datasets for 10 Languages},
  author={Park, Kyubyong and Mulc, Thomas},
  journal={Interspeech},
  year={2019}
}

By Kyubyong Park, Tommy Mulc