5 papers
DiariZen Explained: A Tutorial for the Open Source State-of-the-Art Speaker Diarization Pipeline
Nikhil Raghav
Speaker diarization (SD) is the task of answering "who spoke when" in a multi-speaker audio stream. Classically, an SD system clusters segments of speech belonging to an individual…
TCG CREST System Description for the DISPLACE-M Challenge
Nikhil Raghav, Md Sahidullah
This report presents the TCG CREST system description for Track 1 (Speaker Diarization) of the DISPLACE-M challenge, focusing on naturalistic medical conversations in noisy rural-h…
MK-SGC-SC: Multiple Kernel Guided Sparse Graph Construction in Spectral Clustering for Unsupervised Speaker Diarization
Nikhil Raghav, Avisek Gupta, Swagatam Das +1
Speaker diarization aims to segment audio recordings into regions corresponding to individual speakers. Although unsupervised speaker diarization is inherently challenging, the pro…
The TCG CREST -- RKMVERI Submission for the NCIIPC Startup India AI Grand Challenge
Nikhil Raghav, Arnab Banerjee, Janojit Chakraborty +3
In this report, we summarize the integrated multilingual audio processing pipeline developed by our team for the inaugural NCIIPC Startup India AI GRAND CHALLENGE, addressing Probl…
Self-Tuning Spectral Clustering for Speaker Diarization
Nikhil Raghav, Avisek Gupta, Md Sahidullah +1
Spectral clustering has proven effective in grouping speech representations for speaker diarization tasks, although post-processing the affinity matrix remains difficult due to the…