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README.md
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@@ -141,22 +141,26 @@ The pre-trained `pyannote/embedding` model from `pyannote.audio` was used to ext
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If you use this dataset, please cite the original LibriTTS corpus, as well as `pyannote.audio`.
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```bibtex
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@inproceedings{
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title={LibriTTS: A Corpus
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author={Zen
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}
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@
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year={2020},
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}
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```
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## License
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If you use this dataset, please cite the original LibriTTS corpus, as well as `pyannote.audio`.
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```bibtex
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@inproceedings{zen19_interspeech,
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title = {LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speech},
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author = {Heiga Zen and Viet Dang and Rob Clark and Yu Zhang and Ron J. Weiss and Ye Jia and Zhifeng Chen and Yonghui Wu},
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year = {2019},
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booktitle = {Interspeech 2019},
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pages = {1526--1530},
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doi = {10.21437/Interspeech.2019-2441},
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issn = {2958-1796},
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}
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@INPROCEEDINGS{9052974,
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author={Bredin, Hervé and Yin, Ruiqing and Coria, Juan Manuel and Gelly, Gregory and Korshunov, Pavel and Lavechin, Marvin and Fustes, Diego and Titeux, Hadrien and Bouaziz, Wassim and Gill, Marie-Philippe},
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booktitle={ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
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title={Pyannote.Audio: Neural Building Blocks for Speaker Diarization},
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year={2020},
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volume={},
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number={},
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pages={7124-7128},
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keywords={Voice activity detection;Conferences;Pipelines;Machine learning;Signal processing;Acoustics;Open source software;speaker diarization;voice activity detection;speaker change detection;overlapped speech detection;speaker embedding},
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doi={10.1109/ICASSP40776.2020.9052974}}
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```
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## License
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