Repository: HLTSingapore/Emotional-Speech-Data
Branch: main
Commit: 03e4b7086005
Files: 2
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Directory structure:
gitextract_yncrzj8r/

├── LICENSE
└── README.md

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FILE: LICENSE
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MIT License

Copyright (c) 2020 HLTSingapore

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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The above copyright notice and this permission notice shall be included in all
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SOFTWARE.


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FILE: README.md
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# Publicly Available Emotional Speech Dataset (ESD) for Speech Synthesis and Voice Conversion
This is the GitHub page for publicly available emotional speech dataset (ESD) for speech synthesis and voice conversion.

This dataset contains 350 parallel utterances spoken by 10 native Mandarin speakers, and 10 English speakers with 5 emotional states (neutral, happy, angry, sad and surprise). The transcripts are provided.

# License
Please complete a [License](https://drive.google.com/file/d/1Q1Wa45u-ymzpUO3_U-y8yisn4f5PlDIK/view?usp=sharing) and send it to zhoukun@u.nus.edu. This database can only be used for research purpose.

# Download 
The whole dataset can be downloaded here: [Google Drive](https://drive.google.com/file/d/1scuFwqh8s7KIYAfZW1Eu6088ZAK2SI-v/view?usp=sharing)


Note: For users from mainland China, google drive cannot be accessed. Please send an email to zhoukun@u.nus.edu. We will share this dataset with you through other platforms.

# Paper
If you are using this dataset, please kindly cite this [paper](https://www.sciencedirect.com/science/article/pii/S0167639321001308):
```
@inproceedings{zhou2021seen,
  title={Seen and unseen emotional style transfer for voice conversion with a new emotional speech dataset},
  author={Zhou, Kun and Sisman, Berrak and Liu, Rui and Li, Haizhou},
  booktitle={ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={920--924},
  year={2021},
  organization={IEEE}
}
@article{zhou2021emotional,
title = {Emotional voice conversion: Theory, databases and ESD},
journal = {Speech Communication},
volume = {137},
pages = {1-18},
year = {2022},
issn = {0167-6393}
}
```