Journal ArticleDOI
DISTBIC: a speaker-based segmentation for audio data indexing
P. Delacourt,Christian Wellekens +1 more
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TLDR
This paper proposes a new segmentation method, called DISTBIC, which combines two different segmentation techniques and is efficiency in detecting speaker turns even close to one another (i.e., separated by a few seconds).About:
This article is published in Speech Communication.The article was published on 2000-09-01. It has received 299 citations till now. The article focuses on the topics: Speaker diarisation & Speaker recognition.read more
Citations
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Journal ArticleDOI
A tutorial on text-independent speaker verification
Frédéric Bimbot,Jean-François Bonastre,Corinne Fredouille,Guillaume Gravier,Ivan Magrin-Chagnolleau,Sylvain Meignier,Teva Merlin,Javier Ortega-Garcia,Dijana Petrovska-Delacrétaz,Douglas A. Reynolds +9 more
TL;DR: An introduction proposes a modular scheme of the training and test phases of a speaker verification system, and the most commonly speech parameterization used in speaker verification, namely, cepstral analysis, is detailed.
Journal ArticleDOI
Speaker Diarization: A Review of Recent Research
Xavier Anguera Miro,Simon Bozonnet,Nicholas Evans,Corinne Fredouille,Gerald Friedland,Oriol Vinyals +5 more
TL;DR: An analysis of speaker diarization performance as reported through the NIST Rich Transcription evaluations on meeting data and identify important areas for future research are presented.
Book
MPEG-7 Audio and Beyond: Audio Content Indexing and Retrieval
TL;DR: A comparison of MPEG-7 Audio Spectrum Projection vs. MFCC Features and Results for Distinguishing Between Speech, Music and Environmental Sound shows that the former is superior to the latter in terms of sound classification.
Journal ArticleDOI
Multistage speaker diarization of broadcast news
TL;DR: This paper describes recent advances in speaker diarization with a multistage segmentation and clustering system, which incorporates a speaker identification step, which builds upon the baseline audio partitioner used in the LIMSI broadcast news transcription system.
Journal ArticleDOI
Robust speaker change detection
TL;DR: In this article, the authors present a criterion which can be used to identify speaker changes in an audio stream without such tuning, which consists of calculating the log likelihood ratio (LLR) of two models with the same number of parameters.
References
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Proceedings ArticleDOI
SWITCHBOARD: telephone speech corpus for research and development
TL;DR: SWITCHBOARD as mentioned in this paper is a large multispeaker corpus of conversational speech and text which should be of interest to researchers in speaker authentication and large vocabulary speech recognition.
Speaker, Environment and Channel Change Detection and Clustering via the Bayesian Information Criterion
TL;DR: The segmentation algorithm can successfully detect acoustic changes; the clustering algorithm can produce clusters with high purity, leading to improvements in accuracy through unsupervised adaptation as much as the ideal clustering by the true speaker identities.
Automatic Segmentation, Classification and Clustering of Broadcast News Audio
TL;DR: This work describes the problems faced in adapting a system built to recognize one utterance at a time to a task that requires recognition of an entire half hour show, and shows that a priori knowledge of acoustic conditions and speakers in the broadcast data is not required for segmentation.