ConBiMamba in Speaker Diarization

• ConBiMamba is a novel speaker diarization method that integrates bidirectional processing with self-attention mechanisms to boost clustering accuracy.
• The approach employs dual Mamba frameworks to refine segment boundaries and reduce misclassification in multi-speaker audio environments.
• ConBiMamba offers actionable insights for real-time audio analysis, benefiting applications in telecommunications, forensic analysis, and more.

Searching arXiv for the cited ConBiMamba-related papers and closely related Mamba/backbone papers. arXiv search query: "ConBiMamba speaker diarization bidirectional Mamba self-attention alternative Fake-Mamba VCMamba CCMamba ConMamba"