论文标题
2022 Voxceleb扬声器识别挑战的诊断任务的GIST-AITER系统
GIST-AiTeR System for the Diarization Task of the 2022 VoxCeleb Speaker Recognition Challenge
论文作者
论文摘要
本报告介绍了2022 Voxceleb扬声器识别挑战（VOXSRC）轨道4的GIST-AITER团队的提交系统。我们的系统主要包括语音增强，语音活动检测，嵌入多尺度的扬声器，概率线性判别分析的扬声器扬声器集群和重叠的语音检测模型。我们首先根据不同的模型组合构建四个不同的诊断系统，并提供最佳的实验努力。我们的最终提交是所有四个系统的集合系统，并在挑战评估集中达到了5.12％的诊断错误率，在挑战的诊断轨道上排名第三。
This report describes the submission system of the GIST-AiTeR team at the 2022 VoxCeleb Speaker Recognition Challenge (VoxSRC) Track 4. Our system mainly includes speech enhancement, voice activity detection , multi-scaled speaker embedding, probabilistic linear discriminant analysis-based speaker clustering, and overlapped speech detection models. We first construct four different diarization systems according to different model combinations with the best experimental efforts. Our final submission is an ensemble system of all the four systems and achieves a diarization error rate of 5.12% on the challenge evaluation set, ranked third at the diarization track of the challenge.
