Semi-Supervised Multi-Channel Speaker Diarization With Cross-Channel Attention
Semi-Supervised Multi-Channel Speaker Diarization With Cross-Channel Attention
Most neural speaker diarization systems rely on sufficient manual training data labels, which are hard to collect under real-world scenarios. This paper proposes a semi-supervised speaker diarization system to utilize large-scale multi-channel training data by generating pseudo-labels for unlabeled data. Furthermore, we introduce cross-channel attention into the Neural Speaker Diarization …