Speaker recognition is a task of identifying persons from their voices. Recently, deep
learning has dramatically revolutionized speaker recognition. However, there is lack of …

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 …

The objective of the enrollment process is to modify (adapt) a speaker-independent model
into one that best characterizes the target speaker's vocal tract characteristics. Depending …

In this paper, we are interested in detecting changes in speaker identity, environmental
condition and channel condition; we call this the problem of acoustic change detection. The …

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

We consider the problem of speaker diarization, the problem of segmenting an audio
recording of a meeting into temporal segments corresponding to individual speakers. The …

Advances in technology, such as MP3 players, the Internet and DVDs, have led to the
production, storage and distribution of a wealth of audio signals, including speech, music …

This paper reports on activites at LIMSI over the last few years directed at the transcription of
broadcast news data. We describe our development work in moving from laboratory read …

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