The Kriston AI System for the VoxCeleb Speaker Recognition Challenge 2022
- Kriston AI Lab（克里斯顿人工智能实验室）
- The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））
- National University of Singapore（新加坡国立大学）
机构由 AI 辅助整理，请以论文原文为准。
英文摘要：
This technical report describes our system for track 1, 2 and 4 of the VoxCeleb Speaker Recognition Challenge 2022 (VoxSRC-22). By combining several ResNet variants, our submission for track 1 attained a minDCF of 0:090 with EER 1:401%. By further incorporating three fine-tuned pre-trained models, our submission for track 2 achieved a minDCF of 0:072 with EER 1:119%. For track 4, our system consisted of voice activity detection (VAD), speaker embedding extraction, agglomerative hierarchical clustering (AHC) followed by a re-clustering step based on a Bayesian hidden Markov model and overlapped speech detection and handling. Our submission for track 4 achieved a diarisation error rate (DER) of 4.86%. The submissions all ranked the 2nd places for the corresponding tracks.
