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This paper describes the systems developed by the BUT team for the four tracks of the second DIHARD speech diarization challenge.
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D. Snyder, D. Garcia-Romero, D. Povey, and S. Khudanpur, “Deep neural network embeddings for text-independent speaker verification,” in Proceedings of Interspeech 2017 , August 2017, pp. 999–1003
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2018
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G. Sell, D. Snyder, A. McCree, D. Garcia-Romero, J. Villalba, M. Maciejewski, V. Manohar, N. Dehak, D. Povey, S. Watanabe et al. , “Diarization is hard: Some experiences and lessons learned for the jhu team in the inaugural dihard challenge.” in Proceedings of Interspeech 2018 , 2018, pp. 2808–2812
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2019
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L. D. Consortium, “Dihard corpus,” 2019
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2018
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M. Diez, F. Landini, L. Burget, J. Rohdin, A. Silnova, K. Zmolíková, O. Novotný, K. Veselý, O. Glembek, O. Plchot et al. , “But system for dihard speech diarization challenge 2018.” in Proceedings of Interspeech 2018 , 2018, pp. 2798–2802. [Online]. Available: http://dx.doi.org/10.21437/Interspeech.2018-1749
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Cited alongside, same era.
M. Diez, L. Burget, and P. Matejka, “Speaker diarization based on bayesian hmm with eigenvoice priors,” in Proceedings of Odyssey 2018, The speaker and Language Recognition Workshop , 2018
2018
Cited alongside, same era.
L. Drude, J. Heymann, C. Boeddeker, and R. Haeb-Umbach, “NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing,” in 13. ITG Fachtagung Sprachkommunikation (ITG 2018) , Oct 2018
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2019
Closest in time.
M. Diez and L. Burget, “Analysis of variational bayes eigenvoice hidden markov model based speaker diarization, to be published,” 2019
2019
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D. Snyder, D. Garcia-Romero, G. Sell, A. McCree, D. Povey, and S. Khudanpur, “Speaker recognition for multi-speaker conversations using x-vectors,” in ICASSP , 2019
2019
Closest in time.