An Open-source State-of-the-art Toolbox for Broadcast News Diarization
Mickael Rouvier,Grégor Dupuy,Elie Khoury,Teva Merlin,Sylvain Meignier +4 more
- pp 1477-1481
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This paper presents the LIUM open-source speaker diarization toolbox, mostly dedicated to broadcast news, which includes both Hierarchical Agglomerative Clustering using well-known measures such as BIC and CLR, and the new ILP clustering algorithm using i-vectors.Abstract:
This paper presents the LIUM open-source speaker diarization toolbox, mostly dedicated to broadcast news. This tool includes both Hierarchical Agglomerative Clustering using well-known measures such as BIC and CLR, and the new ILP clustering algorithm using i-vectors. Diarization systems are tested on the French evaluation data from ESTER, ETAPE and REPERE campaigns.read more
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Proceedings ArticleDOI
The Second DIHARD Diarization Challenge: Dataset, Task, and Baselines.
Neville Ryant,Kenneth Church,Christopher Cieri,Alejandrina Cristia,Jun Du,Sriram Ganapathy,Mark Liberman +6 more
TL;DR: The second edition of the DIHARD challenge as discussed by the authors was designed to improve the robustness of speaker diarization systems to variation in recording equipment, noise conditions, and conversational domain.
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Europarl-ST: A Multilingual Corpus For Speech Translation Of Parliamentary Debates
Javier Iranzo-Sánchez,Joan Albert Silvestre-Cerdà,Javier Jorge,Nahuel Roselló,Adrià Giménez,Albert Sanchis,Jorge Civera,Alfons Juan +7 more
TL;DR: A novel multilingual SLT corpus containing paired audio-text samples for SLT from and into 6 European languages, for a total of 30 different translation directions, compiled using the debates held in the European Parliament between 2008 and 2012 is presented.
Proceedings ArticleDOI
Convolutional Neural Network for speaker change detection in telephone speaker diarization system
Marek Hrúz,Zbynek Zajic +1 more
TL;DR: The final results on speaker diarization system indicate that the use of speaker change detection based on CNN is beneficial with relative improvement of diarized error rate by 28 %.
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The Third DIHARD Diarization Challenge
Neville Ryant,Prachi Singh,Venkat Krishnamohan,Rajat Varma,Kenneth Church,Christopher Cieri,Jun Du,Sriram Ganapathy,Mark Liberman +8 more
TL;DR: The third DIHARD challenge, the third in a series of speaker diarization challenges intended to improve the robustness of diarized systems to variation in recording equipment, noise conditions, and conversational domain, is introduced.
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VoxLingua107: a Dataset for Spoken Language Recognition
Jörgen Valk,Tanel Alumäe +1 more
TL;DR: This paper generates semi-random search phrases from language-specific Wikipedia data that are then used to retrieve videos from YouTube for 107 languages and uses the data to build language recognition models for several spoken language identification tasks.
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The ESTER Phase II Evaluation Campaign for the Rich Transcription of French Broadcast News
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TL;DR: This paper gives the final results of the ESTER evaluation campaign which started in 2003 and ended in January 2005, to evaluate automatic broadcast news rich transcription systems for the French language.
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The ESTER 2 Evaluation Campaign for the Rich Transcription of French Radio Broadcasts
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