End-to-End Neural Speaker Diarization with Permutation-Free Objectives

The End-to-End Neural Speaker Diarization dataset is a benchmark for speaker diarization.

Data and Resources

Cite this as

Yusuke Fujita, Naoyuki Kanda, Shota Horiguchi, Kenji Nagamatsu, Shinji Watanabe (2024). Dataset: End-to-End Neural Speaker Diarization with Permutation-Free Objectives. https://doi.org/10.57702/7o28s464

DOI retrieved: December 16, 2024

Additional Info

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Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2205.07086
Author Yusuke Fujita
More Authors
Naoyuki Kanda
Shota Horiguchi
Kenji Nagamatsu
Shinji Watanabe
Homepage https://arxiv.org/abs/1904.04761