Speaker diarization is a task to label audio or video recordings with classes that correspond
to speaker identity, or in short, a task to identify “who spoke when”. In the early years …

Speaker diarization is the task of determining “who spoke when?” in an audio or video
recording that contains an unknown amount of speech and also an unknown number of …

Audio diarization is the process of annotating an input audio channel with information that
attributes (possibly overlap**) temporal regions of signal energy to their specific sources …

In speaker diarization, standard approaches typically perform speaker clustering on some
initial segmentation before refining the segment boundaries in a re-segmentation step to …

This paper presents the LIUM open-source speaker diarization toolbox, mostly dedicated to
broadcast news. This tool includes both Hierarchical Agglomerative Clustering using well …

This paper presents an open-source diarization toolkit which is mostly dedicated to speaker
and developed by the LIUM. This toolkit includes hierarchical agglomerative clustering …

This survey focuses on two challenging speech processing topics, namely: speaker
segmentation and speaker clustering. Speaker segmentation aims at finding speaker …

Speaker indexing or diarization is an important task in audio processing and retrieval.
Speaker diarization is the process of labeling a speech signal with labels corresponding to …

This paper presents the ALIZE/SpkDet open source software packages for text independent
speaker recognition. This software is based on the well-known UBM/GMM approach. It …

This paper studies the segmentation and clustering of speaker speech. In order to improve
the accuracy of speech endpoint detection, the traditional double‐threshold short‐time …