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A Visual Analytics Approach to Finding Factors Improving Automatic Speaker Identifications.

, , , , , and . ICMI, page 323-326. ACM, (2015)

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Segmentation of TV shows into scenes using speaker diarization and speech recognition.. ICASSP, page 2377-2380. IEEE, (2012)pyannote.audio: neural building blocks for speaker diarization., , , , , , , , , and . CoRR, (2019)IRIM at TRECVID 2017: Instance Search., , , , , , , , , and . TRECVID, National Institute of Standards and Technology (NIST), (2017)Brouhaha: Multi-Task Training for Voice Activity Detection, Speech-to-Noise Ratio, and C50 Room Acoustics Estimation., , , , , , , , , and . ASRU, page 1-7. IEEE, (2023)ODESSA/PLUMCOT at Albayzin Multimodal Diarization Challenge 2018., , , , , , , and . IberSPEECH, page 194-198. ISCA, (2018)IRIM at TRECVID 2011 : Semantic Indexing and Instance Search., , , , , , , , , and 14 other author(s). TRECVID, National Institute of Standards and Technology (NIST), (2011)Detecting Replay Attacks in Audiovisual Identity Verification., , , and . ICASSP (1), page 621-624. IEEE, (2006)Lexical speaker identification in TV shows., , , , , and . Multimedia Tools Appl., 74 (4): 1377-1396 (2015)Audio-visual speech asynchrony detection using co-inertia analysis and coupled hidden markov models., , , , and . Pattern Anal. Appl., 12 (3): 271-284 (2009)Powerset multi-class cross entropy loss for neural speaker diarization., and . CoRR, (2023)