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In this paper, we propose a novel end-to-end neural-network-based speaker diarization method.
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N. Kanda
2018
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M. Maciejewski, D. Snyder, V. Manohar, N. Dehak, and S. Khudanpur, “Characterizing performance of speaker diarization systems on far-field speech using standard methods,” in
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2017
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D. Yu, M. Kolbæk, Z. Tan, and J. Jensen, “Permutation invariant training of deep models for speaker-independent multi-talker speech separation,” in
2017
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M. Kolbæk, D. Yu, Z. Tan, and J. Jensen, “Multitalker speech separation with utterance-level permutation invariant training of deep recurrent neural networks,”
2017
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T. Ko, V. Peddinti, D. Povey, M. L. Seltzer, and S. Khudanpur, “A study on data augmentation of reverberant speech for robust speech recognition,” in
2017
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2018
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J. Du, T. Gao, L. Sun, F. Ma, Y. Fang, D.-Y. Liu, Q. Zhang, X. Zhang, H.-K. Wang, J. Pan, J.-Q. Gao, C.-H. Lee, and J.-D. Chen, “The USTC-iFlytek Systems for CHiME-5 Challenge,” in
2018
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C. Boeddeker, J. Heitkaemper, J. Schmalenstroeer, L. Drude, J. Heymann, and R. Haeb-Umbach, “Front-End Processing for the CHiME-5 Dinner Party Scenario,” in
2018
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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, and S. Khudanpur, “Diarization is hard: Some experiences and lessons learned for the JHU team in the inaugural DIHARD challenge,” in
2018
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M. Diez, F. Landini, L. Burget, J. Rohdin, A. Silnova, K. Žmolíková, O. Novotný, K. Veselý, O. Glembek, O. Plchot, L. Mošner, and P. Matějka, “BUT system for DIHARD speech diarization challenge 2018,” in
2018
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2018
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N. Kanda, Y. Fujita, S. Horiguchi, R. Ikeshita, K. Nagamatsu, and S. Watanabe, “Acoustic modeling for distant multi-talker speech recognition with single- and multi-channel branches,” in
2019
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T. von Neumann, K. Kinoshita, M. Delcroix, S. Araki, T. Nakatani, and R. Haeb-Umbach, “All-neural online source separation, counting, and diarization for meeting analysis,” in
2019
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A. Zhang, Q. Wang, Z. Zhu, J. Paisley, and C. Wang, “Fully Supervised Speaker Diarization,” in
2019
Closest in time.