Towards a hybrid approach for Arabic Sentiment AnalysisStarting: 03/10/2016PhD Student: Amira BarhoumiAdvisor(s): Yannick Estève (LIUM, LST)Co-advisor(s): Nathalie Camelin (LIUM, LST) & Lamia Hadrich Belguith (MIRACL, Tunisie)Funding: Agreement “Cotutelle Convention” (LIUM, LST) & (MIRACL, Tunisie)Sentiment analysis is a growing field of research and has been subject of numerous studies. This thesis aims at designing a hybrid […]
Corpus: TED-LIUM Release 3Licence: Creative Commons BY-NC-ND 3.0 (attribution/non-commercial/no-derivatives)Author(s): François FernandezVincent NguyenSahar GhannayNatalia TomashenkoYannick EstèveThis is the TED-LIUM corpus release 3, licensed under Creative Commons BY-NC-ND 3.0 (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.en). All talks and text are property of TED Conferences LLC. This new TED-LIUM release was made through a collaboration between the Ubiqus company and the […]
Corpus: TED-LIUM Release 2Licence: Creative Commons BY-NC-ND 3.0 (attribution/non-commercial/no-derivatives)Author(s): Anthony RousseauPaul DelégliseYannick EstèveThis is the TED-LIUM corpus release 2, licensed under Creative Commons BY-NC-ND 3.0 (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.en). The TED-LIUM corpus was made from audio talks and their transcriptions available on the TED website. We have prepared and filtered these data in order to train acoustic […]
Corpus: TED-LIUM Release 1Licence: Creative Commons BY-NC-ND 3.0 (attribution/non-commercial/no-derivatives)Author(s): Anthony RousseauPaul DelégliseYannick EstèveThis is the TED-LIUM corpus release 1, licensed under Creative Commons BY-NC-ND 3.0 (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.en). The TED-LIUM corpus is English-language TED talks, with transcriptions, sampled at 16kHz. It contains about 118 hours of speech. More details are given in this paper: A. […]
Software: NMTPYLicence: MIT LicenseGitHub: https://github.com/lium-lst/nmtpyURL: https://arxiv.org/abs/1706.00457Author(s): Ozan CaglayanMercedes García MartínezAdrien BardetWalid AransaLoïc BarraultFethi Bougaresnmtpy is a suite of Python tools, primarily based on the starter code provided in dl4mt-tutorial for training neural machine translation networks using Theano. The basic motivation behind forking dl4mt-tutorial was to create a framework where it would be easy to implement […]
Software: NMTPYTORCHLicence: MIT LicenseGitHub: https://github.com/lium-lst/nmtpytorch/URL: https://arxiv.org/abs/1706.00457Author(s): Ozan CaglayanMercedes García MartínezAdrien BardetWalid AransaFethi BougaresLoïc BarraultThis is the PyTorch fork of nmtpy, a sequence-to-sequence framework which was originally a fork of dl4mt-tutorial.
Software: LIUM Speaker DiarizationLicence: GPLURL: https://projets-lium.univ-lemans.fr/spkdiarization/Outil de segmentation et regroupement locuteur (Speaker diarization) en java.
Software: SIDEKITLicence: LGPLGitHub: https://git-lium.univ-lemans.fr/Larcher/sidekitURL: https://projets-lium.univ-lemans.fr/sidekit/Author(s): Anthony LarcherKong Aik LeeSylvain Meignier Welcome to SIDEKIT documentation! SIDEKIT is an open source package for Speaker and Language recognition. The aim of SIDEKIT is to provide an educational and efficient toolkit for speaker/language recognition including the whole chain of treatment that goes from the audio data to the analysis […]
Software: SIDEKIT for diarization (s4d)Licence: LGPLGitHub: https://git-lium.univ-lemans.fr/Meignier/s4dURL: https://projets-lium.univ-lemans.fr/s4d/Author(s): Pierre-Alexandre BrouxFlorent DesnousAnthony LarcherSylvain Meignier Welcome to SIDEKIT for diarization documentation! SIDEKIT for diarization (s4d as short name) is an open source package extension of SIDEKIT for Speaker diarization . The aim of S4D is to provide an educational and efficient toolkit for speaker diarization including the […]
Thematic segmentation of automatic transcriptions and enrichment of educational documents in a lecture contextStarting: 23/01/2017PhD Student: Salima MdhaffarAdvisor(s): Yannick Estève (LIUM, LST)Co-advisor(s): Antoine Laurent (LIUM, LST), Nicolas Hernandez (LS2N), Solen Quiniou (LS2N)Funding: ANR PASTEL ProjectThis thesis is a part of the PASTEL project (Performing Automated Speech Transcription for Enhancing Learning), which aims to explore the […]
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