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Communication Dans Un Congrès Année : 2020

Speaker detection in the wild: Lessons learned from JSALT 2019

Ling Guo
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Koji Okabe
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Saurabh Kataria
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Résumé

This paper presents the problems and solutions addressed at the JSALT workshop when using a single microphone for speaker detection in adverse scenarios. The main focus was to tackle a wide range of conditions that go from meetings to wild speech. We describe the research threads we explored and a set of modules that was successful for these scenarios. The ultimate goal was to explore speaker detection; but our first finding was that an effective diarization improves detection, and not having a diarization stage impoverishes the performance. All the different configurations of our research agree on this fact and follow a main backbone that includes diarization as a previous stage. With this backbone, we analyzed the following problems: voice activity detection, how to deal with noisy signals, domain mismatch, how to improve the clustering; and the overall impact of previous stages in the final speaker detection. In this paper, we show partial results for speaker diarizarion to have a better understanding of the problem and we present the final results for speaker detection.
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Dates et versions

hal-02417632 , version 1 (20-12-2019)

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Paola García, Jesus Villalba, Hervé Bredin, Jun Du, Diego Castan, et al.. Speaker detection in the wild: Lessons learned from JSALT 2019. Odyssey 2020 The Speaker and Language Recognition Workshop, Nov 2020, Tokyo, Japan. ⟨hal-02417632⟩
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