His primary areas of study are Artificial intelligence, Speech recognition, Natural language processing, Hidden Markov model and French. His Artificial intelligence study combines topics in areas such as Computer vision and Pattern recognition. His Speech recognition research is multidisciplinary, relying on both Artificial neural network, Segmentation, Word and Support vector machine.
The various areas that Guillaume Gravier examines in his Natural language processing study include Speaker diarisation and Audio mining. His work carried out in the field of Speaker diarisation brings together such families of science as Normalization and Cluster analysis. Guillaume Gravier studied Hidden Markov model and Audio-visual speech recognition that intersect with Facial recognition system, Usability, Feature extraction and Speechreading.
His main research concerns Artificial intelligence, Speech recognition, Natural language processing, Pattern recognition and Multimedia. His studies in Artificial intelligence integrate themes in fields like Machine learning and Computer vision. The Speech recognition study combines topics in areas such as Search engine indexing and Robustness.
His Natural language processing study combines topics from a wide range of disciplines, such as Transcription and Word. His work is dedicated to discovering how Pattern recognition, Cluster analysis are connected with Unsupervised learning and other disciplines. His Multimedia study also includes
Guillaume Gravier spends much of his time researching Artificial intelligence, Hyperlink, Artificial neural network, Multimedia and Information retrieval. Guillaume Gravier has included themes like Machine learning and Natural language processing in his Artificial intelligence study. His work on Conditional random field as part of general Natural language processing research is frequently linked to Label propagation, thereby connecting diverse disciplines of science.
Guillaume Gravier works mostly in the field of Artificial neural network, limiting it down to concerns involving Convolutional neural network and, occasionally, Optical flow and Computer vision. His research in Multimedia focuses on subjects like World Wide Web, which are connected to Big data. The Relevance research Guillaume Gravier does as part of his general Information retrieval study is frequently linked to other disciplines of science, such as RDF, therefore creating a link between diverse domains of science.
Guillaume Gravier mainly focuses on Artificial intelligence, Artificial neural network, Deep learning, Crossmodal and Feature learning. His studies deal with areas such as Motion, Convolutional neural network and Anticipation as well as Artificial neural network. His Convolutional neural network research is multidisciplinary, incorporating perspectives in Optical flow, Robot, Video tracking and Computer vision.
The study incorporates disciplines such as Sentence, Spoken language, Natural language processing, Word and Dialog box in addition to Deep learning. Guillaume Gravier has researched Feature learning in several fields, including Class and Ensemble learning. His Autoencoder research includes elements of Word2vec, Embedding, Speech recognition, Query expansion and Pattern recognition.
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A tutorial on text-independent speaker verification
Frédéric Bimbot;Jean-François Bonastre;Corinne Fredouille;Guillaume Gravier.
EURASIP Journal on Advances in Signal Processing (2004)
Recent advances in the automatic recognition of audiovisual speech
G. Potamianos;C. Neti;G. Gravier;A. Garg.
Proceedings of the IEEE (2003)
The ESTER Phase II Evaluation Campaign for the Rich Transcription of French Broadcast News
Sylvain Galliano;Edouard Geoffrois;Djamel Mostefa;Khalid Choukri.
conference of the international speech communication association (2005)
The ESTER 2 Evaluation Campaign for the Rich Transcription of French Radio Broadcasts
Sylvain Galliano;Guillaume Gravier;Laura Chaubard.
conference of the international speech communication association (2009)
The ETAPE corpus for the evaluation of speech-based TV content processing in the French language
Guillaume Gravier;Gilles Adda;Niklas Paulsson;Matthieu Carr'e.
language resources and evaluation (2012)
Corpus description of the ESTER Evaluation Campaign for the Rich Transcription of French Broadcast News
Sylvain Galliano;Edouard Geoffrois;Guillaume Gravier;Jean-François Bonastre.
language resources and evaluation (2006)
Speaker diarization using bottom-up clustering based on a parameter-derived distance between adapted GMMs.
Michael Betser;Frédéric Bimbot;Mathieu Ben;Guillaume Gravier.
conference of the international speech communication association (2004)
HMM based structuring of tennis videos using visual and audio cues
E. Kijak;G. Gravier;P. Gros;L. Oisel.
international conference on multimedia and expo (2003)
Audiovisual integration for tennis broadcast structuring
Ewa Kijak;Guillaume Gravier;Lionel Oisel;Patrick Gros.
Multimedia Tools and Applications (2006)
The ESTER Evaluation Campaign for the Rich Transcription of French Broadcast News
Guillaume Gravier;Jean-François Bonastre;Edouard Geoffrois;Sylvain Galliano.
language resources and evaluation (2004)
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