Thierry Dutoit focuses on Speech recognition, Speech synthesis, Artificial intelligence, Speech processing and Electroencephalography. Thierry Dutoit studies Speech recognition, focusing on Speech coding in particular. His research in Speech synthesis is mostly focused on MBROLA.
His Artificial intelligence research is multidisciplinary, incorporating elements of Natural language processing, Machine learning and Pattern recognition. The various areas that Thierry Dutoit examines in his Speech processing study include Event, Noise, Filter and Robustness. His work on Brain–computer interface as part of general Electroencephalography research is frequently linked to Assessment methods, bridging the gap between disciplines.
His main research concerns Speech recognition, Artificial intelligence, Speech synthesis, Hidden Markov model and Speech processing. His studies deal with areas such as Feature extraction and Laughter as well as Speech recognition. His work investigates the relationship between Artificial intelligence and topics such as Pattern recognition that intersect with problems in Artificial neural network.
His Speech synthesis study focuses on MBROLA in particular. His studies in Hidden Markov model integrate themes in fields like Articulation, Motion capture and Interpolation. In his study, which falls under the umbrella issue of Speech processing, Waveform is strongly linked to Robustness.
His primary scientific interests are in Speech recognition, Artificial intelligence, Speech synthesis, Deep learning and Hidden Markov model. His primary area of study in Speech recognition is in the field of Speech processing. His Artificial intelligence study combines topics in areas such as Machine learning and Computer vision.
His Speech synthesis research is multidisciplinary, relying on both Recurrent neural network, Parametric statistics, Interpolation, Algorithm and Style. His Deep learning research includes themes of Leverage, Natural language processing, Field, View synthesis and Visualization. In his study, Principal component analysis is inextricably linked to Quality, which falls within the broad field of Hidden Markov model.
Thierry Dutoit mostly deals with Artificial intelligence, Speech synthesis, Deep learning, Field and Human–computer interaction. Thierry Dutoit combines topics linked to Computer vision with his work on Artificial intelligence. The concepts of his Speech synthesis study are interwoven with issues in Recurrent neural network, Parametric statistics, Natural language processing, Visualization and Algorithm.
His Deep learning research includes elements of Speech recognition, Representation, Leverage and Interpolation. He has researched Field in several fields, including Sorting and View synthesis. Thierry Dutoit combines subjects such as Perception, Clickable, Interface and Plot with his study of Human–computer interaction.
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An introduction to text-to-speech synthesis
The MBROLA project: towards a set of high quality speech synthesizers free of use for non commercial purposes
T. Dutoit;V. Pagel;N. Pierret;F. Bataille.
international conference on spoken language processing (1996)
Performance of the Emotiv Epoc headset for P300-based applications
Matthieu Duvinage;Thierry Castermans;Mathieu Petieau;Thomas Hoellinger.
Biomedical Engineering Online (2013)
Traitement de la Parole
R. Boite;Hervé Bourlard;T. Dutoit;J. Hancq.
MBR-PSOLA: Text-To-Speech synthesis based on an MBE re-synthesis of the segments database
T. Dutoit;H. Leich.
Speech Communication (1993)
Detection of Glottal Closure Instants From Speech Signals: A Quantitative Review
T. Drugman;M. Thomas;J. Gudnason;P. Naylor.
IEEE Transactions on Audio, Speech, and Language Processing (2012)
Saliency and Human Fixations: State-of-the-Art and Study of Comparison Metrics
Nicolas Riche;Matthieu Duvinage;Matei Mancas;Bernard Gosselin.
international conference on computer vision (2013)
A probabilistic framework for dialog simulation and optimal strategy learning
O. Pietquin;T. Dutoit.
IEEE Transactions on Audio, Speech, and Language Processing (2006)
RARE2012: A multi-scale rarity-based saliency detection with its comparative statistical analysis
Nicolas Riche;Matei Mancas;Matthieu Duvinage;Makiese Mibulumukini.
Signal Processing-image Communication (2013)
Glottal closure and opening instant detection from speech signals.
Thomas Drugman;Thierry Dutoit.
conference of the international speech communication association (2009)
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