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  This is a massively multilingual conformer-based speaker recognition model.
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- The model was trained with public data only.
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- The paper: https://arxiv.org/abs/2104.02125
 
 
 
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  ```
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  @inproceedings{chojnacka2021speakerstew,
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  title={{SpeakerStew: Scaling to many languages with a triaged multilingual text-dependent and text-independent speaker verification system}},
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  author={Chojnacka, Roza and Pelecanos, Jason and Wang, Quan and Moreno, Ignacio Lopez},
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  booktitle={Prod. Interspeech},
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- year={2021}
 
 
 
 
 
 
 
 
 
 
 
 
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  }
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  ```
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  This is a massively multilingual conformer-based speaker recognition model.
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+ The model was trained with public data only, using the GE2E loss.
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+ Paper:
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+
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+ * Multilingual: https://arxiv.org/abs/2104.02125
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+ * GE2E loss: https://arxiv.org/abs/1710.10467
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  ```
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  @inproceedings{chojnacka2021speakerstew,
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  title={{SpeakerStew: Scaling to many languages with a triaged multilingual text-dependent and text-independent speaker verification system}},
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  author={Chojnacka, Roza and Pelecanos, Jason and Wang, Quan and Moreno, Ignacio Lopez},
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  booktitle={Prod. Interspeech},
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+ pages={1064--1068},
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+ year={2021},
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+ doi={10.21437/Interspeech.2021-646},
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+ issn={2958-1796},
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+ }
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+
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+ @inproceedings{wan2018generalized,
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+ title={Generalized end-to-end loss for speaker verification},
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+ author={Wan, Li and Wang, Quan and Papir, Alan and Moreno, Ignacio Lopez},
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+ booktitle={International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
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+ pages={4879--4883},
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+ year={2018},
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+ organization={IEEE}
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  }
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  ```
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