Overlap-aware diarization: Resegmentation using neural end-to-end overlapped speech detection - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2020

Overlap-aware diarization: Resegmentation using neural end-to-end overlapped speech detection

Résumé

We address the problem of effectively handling overlapping speech in a diarization system. First, we detail a neural Long Short-Term Memory- based architecture for overlap detection. Secondly, detected overlap regions are exploited in conjunction with a frame-level speaker posterior matrix to make two-speaker assignments for overlapped frames in the resegmentation step. The overlap detection module achieves state-of-the-art performance on the AMI, DIHARD, and ETAPE corpora. We apply overlap-aware resegmentation on AMI, resulting in a 20% relative DER reduction over the baseline system. While this approach is by no means an end-all solution to overlap-aware diarization, it reveals promising directions for handling overlap.

Dates et versions

hal-02995367 , version 1 (09-11-2020)

Identifiants

Citer

Latanã© Bullock, Hervé Bredin, Leibny-Paola Garcia-Perera. Overlap-aware diarization: Resegmentation using neural end-to-end overlapped speech detection. IEEE International Conference on Acoustics, Speech, and Signal Processing, May 2020, Barcelona, Spain. ⟨hal-02995367⟩
146 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More