The Newsbridge -Telecom SudParis VoxCeleb Speaker Recognition Challenge 2022 System Description
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Abstract (arXiv)
We describe the system used by our team for the VoxCeleb Speaker Recognition Challenge 2022 (VoxSRC 2022) in the speaker diarization track. Our solution was designed around a new combination of voice activity detection algorithms that uses the strengths of several systems. We introduce a novel multi stream approach with a decision protocol based on classifiers entropy. We called this method a multi-stream voice activity detection and used it with standard baseline diarization embeddings, clustering and resegmentation. With this work, we successfully demonstrated that using a strong baseline and working only on voice activity detection, one can achieved close to state-of-theart results.
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References · 8
- 2015Deep Residual Learning for Image Recognitioncited by 51,809
- 2017VoxCeleb: a large-scale speaker identification datasetcited by 714
- 2019pyannote.audio: neural building blocks for speaker diarizationcited by 175
- 2021A Review of Speaker Diarization: Recent Advances with Deep Learningcited by 122
- 2020Bayesian HMM clustering of x-vector sequences (VBx) in speaker diarization: theory, implementation and analysis on standard taskscited by 69
- 2019Overlap-aware diarization: resegmentation using neural end-to-end overlapped speech detectioncited by 26
- 2019End-to-end Domain-Adversarial Voice Activity Detectioncited by 11
- 2020Analysis of the BUT Diarization System for VoxConverse Challengecited by 11
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