R{\'e}seaux Bay{\'e}siens Dynamiques pour la Reconnaissance Multi-Bandes de la Parole

@inproceedings{daoudi:inria-00099452,
 abstract = {This paper presents a new approach to multi-band automatic speech recognition which has the advantage to overcome many limitations of classical muti-band systems. The principle of this new approach is to build a speech model in the time-frequency domain using the formalism of Bayesian networks. Contrarily to classical multi-band modeling, this formalism leads to a probabilistic speech model which allows communications between the different sub-bands and, consequently, no recombination step is required in recognition. We develop efficient learning and decoding algorithms and present illustrative experiments on a connected digit recognition task. The experiments show that the Bayesian network's approach is very promising in the field of noisy speech recognition.},
 address = {Nancy, France},
 author = {Daoudi, Khalid and Fohr, Dominique and Antoine, Christophe},
 booktitle = {{XXIVe Journ{\'e}es d'Etudes sur la Parole - JEP'2002}},
 hal_id = {inria-00099452},
 hal_local_reference = {A02-R-257 || daoudi02d},
 hal_version = {v1},
 keywords = {bayesian networks ; reconnaissance de la parole ; speech recognition ; r{\'e}seaux bay{\'e}siens},
 month = {June},
 note = {Colloque avec actes et comit{\'e} de lecture. nationale.},
 organization = {{Equipe Parole - LORIA}},
 pages = {4 p},
 pdf = {https://hal.inria.fr/inria-00099452/file/A02-R-257.pdf},
 title = {{R{\'e}seaux Bay{\'e}siens Dynamiques pour la Reconnaissance Multi-Bandes de la Parole}},
 url = {https://hal.inria.fr/inria-00099452},
 year = {2002}
}