4 citations · 4 across the 2 of their papers we have counts for
7 papers · 1 filter
Self-Supervised Metric Learning With Graph Clustering For Speaker Diarization
Prachi Singh, Sriram Ganapathy
In this paper, we propose a novel algorithm for speaker diarization using metric learning for graph based clustering. The graph clustering algorithms use an adjacency matrix consis…
Self-supervised Representation Learning With Path Integral Clustering For Speaker Diarization
Prachi Singh, Sriram Ganapathy
Automatic speaker diarization techniques typically involve a two-stage processing approach where audio segments of fixed duration are converted to vector representations in the fir…
LEAP Submission for the Third DIHARD Diarization Challenge
Prachi Singh, Rajat Varma, Venkat Krishnamohan +2
The LEAP submission for DIHARD-III challenge is described in this paper. The proposed system is composed of a speech bandwidth classifier, and diarization systems fine-tuned for na…
The Third DIHARD Diarization Challenge
Neville Ryant, Prachi Singh, Venkat Krishnamohan +6
DIHARD III was the third in a series of speaker diarization challenges intended to improve the robustness of diarization systems to variability in recording equipment, noise condit…
Deep Self-Supervised Hierarchical Clustering for Speaker Diarization
Prachi Singh, Sriram Ganapathy
The state-of-the-art speaker diarization systems use agglomerative hierarchical clustering (AHC) which performs the clustering of previously learned neural embeddings. While the cl…
Pairwise Discriminative Neural PLDA for Speaker Verification
Shreyas Ramoji, Prashant Krishnan, Prachi Singh +1
The state-of-art approach to speaker verification involves the extraction of discriminative embeddings like x-vectors followed by a generative model back-end using a probabilistic…