18 citations · 33 across the 13 of their papers we have counts for
13 papers · 1 filter
SphereVBx: Spherical Variational Bayes Clustering for Simplified EEND-VC Diarization
Petr Pálka, Jiangyu Han, Prachi Singh +3
We propose SphereVBx, a Bayesian clustering framework for hyperspherical embeddings based on Toroidal Probabilistic Spherical Discriminant Analysis (T-PSDA). The method follows the…
BUT System Description for CHiME-9 MCoRec Challenge
Dominik Klement, Alexander Polok, Nguyen Hai Phong +2
Multi-talker automatic speech recognition (ASR) in conversational recordings remains an open problem, particularly in scenarios with large portion of overlapping speech where ident…
The Second DISPLACE Challenge : DIarization of SPeaker and LAnguage in Conversational Environments
Shareef Babu Kalluri, Prachi Singh, Pratik Roy Chowdhuri +8
The DIarization of SPeaker and LAnguage in Conversational Environments (DISPLACE) 2024 challenge is the second in the series of DISPLACE challenges, which involves tasks of speaker…
End-to-End Supervised Hierarchical Graph Clustering for Speaker Diarization
Prachi Singh, Sriram Ganapathy
Speaker diarization, the task of segmenting an audio recording based on speaker identity, constitutes an important speech pre-processing step for several downstream applications.Th…
Summary of the DISPLACE Challenge 2023 - DIarization of SPeaker and LAnguage in Conversational Environments
Shikha Baghel, Shreyas Ramoji, Somil Jain +4
In multi-lingual societies, where multiple languages are spoken in a small geographic vicinity, informal conversations often involve mix of languages. Existing speech technologies…
DISPLACE Challenge: DIarization of SPeaker and LAnguage in Conversational Environments
Shikha Baghel, Shreyas Ramoji, Sidharth +8
In multilingual societies, social conversations often involve code-mixed speech. The current speech technology may not be well equipped to extract information from multi-lingual mu…
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…
LEAP System for SRE19 CTS Challenge -- Improvements and Error Analysis
Shreyas Ramoji, Prashant Krishnan, Bhargavram Mysore +2
The NIST Speaker Recognition Evaluation - Conversational Telephone Speech (CTS) challenge 2019 was an open evaluation for the task of speaker verification in challenging conditions…