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Found 5 papers, 1 papers with code
Online Target Speaker Voice Activity Detection for Speaker Diarization
We iteratively extract the results for each block and update the target speaker embedding until reaching the end of the signal.
The DKU-DukeECE-Lenovo System for the Diarization Task of the 2021 VoxCeleb Speaker Recognition Challenge
This report describes the submission of the DKU-DukeECE-Lenovo team to the VoxCeleb Speaker Recognition Challenge (VoxSRC) 2021 track 4.
Sparsely Overlapped Speech Training in the Time Domain: Joint Learning of Target Speech Separation and Personal VAD Benefits
This paper proposes the weighted SI-SNR loss, together with the joint learning of target speech separation and personal VAD.
DIHARD II is Still Hard: Experimental Results and Discussions from the DKU-LENOVO Team
Our diarization system includes multiple modules, namely voice activity detection (VAD), segmentation, speaker embedding extraction, similarity scoring, clustering, resegmentation and overlap detection.
LSTM based Similarity Measurement with Spectral Clustering for Speaker Diarization
More and more neural network approaches have achieved considerable improvement upon submodules of speaker diarization system, including speaker change detection and segment-wise speaker embedding extraction.
