Reconnaissance de la parole pour les locuteurs non natifs en pr{\'e}sence de bruit

@inproceedings{fohr:inria-00100780,
 abstract = {In real world applications, speech recognition is confronted with two main difficulties: the non native speakers and the background noise. The aim of this paper is to compare on the same noisy database different methods in order to increase the robustness of our HMM-based automatic speech recognition system. To deal with the non native speakers, we have tested two solutions: multi-models and adaptation techniques. For noisy speech, we have evaluated two types of methods: the first one (PMC and MLLR) adapts the initial models, trained in clean speech, with a few noisy sentences. The second one (RATZ and MCR) tries to remove the noise from the signal without modifying the HMM models.},
 address = {Nancy, France},
 author = {Fohr, Dominique and Mella, Odile and Illina, Irina and Lauri, Fabrice and Cerisara, Christophe and Antoine, Christophe},
 booktitle = {{XXIV{\`e}mes Journ{\'e}es d'Etude sur la Parole - JEP'02}},
 hal_id = {inria-00100780},
 hal_local_reference = {A02-R-112 || fohr02a},
 hal_version = {v1},
 keywords = {automatic speech recognition ; non native speakers ; parole bruit{\'e}e ; locuteurs non natives ; background noise ; reconnaissance automatique de la parole},
 month = {June},
 note = {Colloque avec actes et comit{\'e} de lecture. nationale.},
 pages = {297-301},
 title = {{Reconnaissance de la parole pour les locuteurs non natifs en pr{\'e}sence de bruit}},
 url = {https://hal.inria.fr/inria-00100780},
 year = {2002}
}