论文标题
但是第二次Dihard语音诊断挑战的系统
BUT System for the Second DIHARD Speech Diarization Challenge
论文作者
论文摘要
本文介绍了BUT团队为第二次Dihard语音诊断挑战的四首曲目开发的获胜系统。对于轨道1和2，该系统主要基于X-VECTORS的执行集聚层次聚类（AHC），然后是基于贝叶斯隐藏的Markov模型和变异贝叶斯推断的另一个X-Vector聚类。我们提供了每个步骤给出的改进的比较，并分享了系统核心的实现。对于第五次循环挑战的录音3和4，我们探索了进行多通道诊断的不同方法，并且在将AHC应用于每个通道概率线性判别分析分析分析分析分析时获得了最佳性能。
This paper describes the winning systems developed by the BUT team for the four tracks of the Second DIHARD Speech Diarization Challenge. For tracks 1 and 2 the systems were mainly based on performing agglomerative hierarchical clustering (AHC) of x-vectors, followed by another x-vector clustering based on Bayes hidden Markov model and variational Bayes inference. We provide a comparison of the improvement given by each step and share the implementation of the core of the system. For tracks 3 and 4 with recordings from the Fifth CHiME Challenge, we explored different approaches for doing multi-channel diarization and our best performance was obtained when applying AHC on the fusion of per channel probabilistic linear discriminant analysis scores.
