H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 32 Citations 4,590 197 World Ranking 7425 National Ranking 190

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Linguistics
  • Speech recognition

His primary areas of investigation include Speech recognition, Artificial intelligence, Natural language processing, Speech processing and Speaker recognition. His study in the fields of Transcription, Speaker diarisation, Word error rate and Voice activity detection under the domain of Speech recognition overlaps with other disciplines such as Sound detection. While the research belongs to areas of Transcription, he spends his time largely on the problem of NIST, intersecting his research to questions surrounding Segmentation.

His study in the field of Word also crosses realms of Resource. His Natural language processing study combines topics in areas such as Speech corpus and Languages of Africa. His Speaker recognition research includes elements of Feature extraction, Motion compensation, TIMIT and Noise.

His most cited work include:

  • Automatic speech recognition for under-resourced languages: A survey (243 citations)
  • The zero resource speech challenge 2017 (123 citations)
  • Listen and Translate: A Proof of Concept for End-to-End Speech-to-Text Translation (116 citations)

What are the main themes of his work throughout his whole career to date?

Laurent Besacier mainly investigates Artificial intelligence, Speech recognition, Natural language processing, Machine translation and Language model. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning and Pattern recognition. The Speech recognition study combines topics in areas such as Segmentation and Speech translation.

His work carried out in the field of Natural language processing brings together such families of science as Pronunciation, Context, Speech corpus and Languages of Africa. Laurent Besacier has researched Machine translation in several fields, including Decoding methods and Rule-based machine translation. Laurent Besacier usually deals with Language model and limits it to topics linked to Acoustic model and Voice activity detection.

He most often published in these fields:

  • Artificial intelligence (55.33%)
  • Speech recognition (50.41%)
  • Natural language processing (45.90%)

What were the highlights of his more recent work (between 2016-2021)?

  • Artificial intelligence (55.33%)
  • Speech recognition (50.41%)
  • Natural language processing (45.90%)

In recent papers he was focusing on the following fields of study:

Laurent Besacier mainly focuses on Artificial intelligence, Speech recognition, Natural language processing, Word and Machine translation. Artificial intelligence is closely attributed to Machine learning in his work. His research on Speech recognition focuses in particular on Language model.

Laurent Besacier has included themes like Similarity and Zero in his Natural language processing study. His Word research incorporates themes from Context, Segmentation and Syllable. His studies deal with areas such as Decoding methods and Image retrieval as well as Machine translation.

Between 2016 and 2021, his most popular works were:

  • The zero resource speech challenge 2017 (123 citations)
  • End-to-End Automatic Speech Translation of Audiobooks (79 citations)
  • FlauBERT: Unsupervised Language Model Pre-training for French (32 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Linguistics
  • Programming language

His main research concerns Artificial intelligence, Natural language processing, Speech recognition, Word and Sentence. His Artificial intelligence study incorporates themes from State and Pattern recognition. Natural language processing is represented through his Parsing and Language model research.

His Speech recognition research includes themes of End-to-end principle and Speech translation. His studies in End-to-end principle integrate themes in fields like Transcription, Decoding methods, Training set and Target text. His Sentence research is multidisciplinary, incorporating elements of Plagiarism detection, Word-sense disambiguation, Similarity, Contextualization and French.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Automatic speech recognition for under-resourced languages: A survey

Laurent Besacier;Etienne Barnard;Alexey Karpov;Tanja Schultz.
Speech Communication (2014)

373 Citations

Step-by-step and integrated approaches in broadcast news speaker diarization

Sylvain Meignier;Sylvain Meignier;Daniel Moraru;Corinne Fredouille;Jean-François Bonastre.
Computer Speech & Language (2006)

173 Citations

Listen and Translate: A Proof of Concept for End-to-End Speech-to-Text Translation

Alexandre Bérard;Olivier Pietquin;Laurent Besacier;Christophe Servan.
neural information processing systems (2016)

165 Citations

Information extraction from sound for medical telemonitoring

D. Istrate;E. Castelli;M. Vacher;L. Besacier.
international conference of the ieee engineering in medicine and biology society (2006)

157 Citations

The zero resource speech challenge 2017

Ewan Dunbar;Xuan Nga Cao;Juan Benjumea;Julien Karadayi.
2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU) (2017)

147 Citations

Automatic sound detection and recognition for noisy environment

Alain Dufaux;Laurent Besacier;Michael Ansorge;Fausto Pellandini.
european signal processing conference (2000)

143 Citations

End-to-End Automatic Speech Translation of Audiobooks

Alexandre Berard;Laurent Besacier;Ali Can Kocabiyikoglu;Olivier Pietquin.
international conference on acoustics, speech, and signal processing (2018)

110 Citations

FlauBERT: Unsupervised Language Model Pre-training for French

Hang Le;Loïc Vial;Jibril Frej;Vincent Segonne.
language resources and evaluation (2019)

110 Citations

GSM speech coding and speaker recognition

L. Besacier;S. Grassi;A. Dufaux;M. Ansorge.
international conference on acoustics, speech, and signal processing (2000)

103 Citations

Automatic Speech Recognition for Under-Resourced Languages: Application to Vietnamese Language

Viet-Bac Le;L. Besacier.
IEEE Transactions on Audio, Speech, and Language Processing (2009)

100 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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