ABSP System for The Third DIHARD Challenge
This is an incremental improvement for speech processing researchers working on speaker diarization in diverse acoustic environments.
The paper tackled speaker diarization by developing an acoustic domain identification system and domain-dependent processing, achieving relative improvements of 9.63% and 10.64% in DER for core and full conditions on the DIHARD III evaluation set.
This report describes the speaker diarization system developed by the ABSP Laboratory team for the third DIHARD speech diarization challenge. Our primary contribution is to develop acoustic domain identification (ADI) system for speaker diarization. We investigate speaker embeddings based ADI system. We apply a domain-dependent threshold for agglomerative hierarchical clustering. Besides, we optimize the parameters for PCA-based dimensionality reduction in a domain-dependent way. Our method of integrating domain-based processing schemes in the baseline system of the challenge achieved a relative improvement of $9.63\%$ and $10.64\%$ in DER for core and full conditions, respectively, for Track 1 of the DIHARD III evaluation set.