# The Newsbridge -Telecom SudParis VoxCeleb Speaker Recognition Challenge 2022 System Description

arXiv: https://arxiv.org/abs/2301.07491 · HTML: https://mlsanity.com/paper/2301.07491/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 15 references that are in the map.
- First posted on arXiv 17 Jan 2023.

## Builds on (most cited first, 8 of 8)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [VoxCeleb: a large-scale speaker identification dataset](https://mlsanity.com/paper/1706.08612/) (2017)
- [pyannote.audio: neural building blocks for speaker diarization](https://mlsanity.com/paper/1911.01255/) (2019)
- [A Review of Speaker Diarization: Recent Advances with Deep Learning](https://mlsanity.com/paper/2101.09624/) (2021)
- [Bayesian HMM clustering of x-vector sequences (VBx) in speaker diarization: theory, implementation and analysis on standard tasks](https://mlsanity.com/paper/2012.14952/) (2020)
- [Overlap-aware diarization: resegmentation using neural end-to-end overlapped speech detection](https://mlsanity.com/paper/1910.11646/) (2019)
- [End-to-end Domain-Adversarial Voice Activity Detection](https://mlsanity.com/paper/1910.10655/) (2019)
- [Analysis of the BUT Diarization System for VoxConverse Challenge](https://mlsanity.com/paper/2010.11718/) (2020)

## 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.