Speaker recognition based on deep learning: An overview
Speaker recognition is a task of identifying persons from their voices. Recently, deep
learning has dramatically revolutionized speaker recognition. However, there is lack of …
learning has dramatically revolutionized speaker recognition. However, there is lack of …
Towards neural diarization for unlimited numbers of speakers using global and local attractors
Attractor-based end-to-end diarization is achieving comparable accuracy to the carefully
tuned conventional clustering-based methods on challenging datasets. However, the main …
tuned conventional clustering-based methods on challenging datasets. However, the main …
Online end-to-end neural diarization with speaker-tracing buffer
This paper proposes a novel online speaker diarization algorithm based on a fully
supervised self-attention mechanism (SA-EEND). Online diarization inherently presents a …
supervised self-attention mechanism (SA-EEND). Online diarization inherently presents a …
Multi-speaker and wide-band simulated conversations as training data for end-to-end neural diarization
End-to-end diarization presents an attractive alternative to standard cascaded diarization
systems because a single system can handle all aspects of the task at once. Many flavors of …
systems because a single system can handle all aspects of the task at once. Many flavors of …
From Modular to End-to-End Speaker Diarization
F Landini - arxiv preprint arxiv:2407.08752, 2024 - arxiv.org
Speaker diarization is usually referred to as the task that determines``who spoke when''in a
recording. Until a few years ago, all competitive approaches were modular. Systems based …
recording. Until a few years ago, all competitive approaches were modular. Systems based …