Continuous Multi-Band Speech Recognition using Bayesian Networks
Khalid Daoudi and Dominique Fohr and Christophe Antoine. ( 2001 )
in: IEEE Automatic Speech Recognition and Understanding Workshop - ASRU'2001, IEEE, pages 4 p
Abstract
Using the Bayesian networks framework, we present a new multi-band approach for continuous speech recognition. This new approach has the advantage to overcome all the limitations of the standard multi-band techniques. Moreover, it leads to a higher fidelity speech modeling than HMMs. We provide a preliminary evaluation of the performance of our new approach on a connected digits recognition task.
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BibTeX Reference
@inproceedings{daoudi:inria-00107521, abstract = {Using the Bayesian networks framework, we present a new multi-band approach for continuous speech recognition. This new approach has the advantage to overcome all the limitations of the standard multi-band techniques. Moreover, it leads to a higher fidelity speech modeling than HMMs. We provide a preliminary evaluation of the performance of our new approach on a connected digits recognition task.}, address = {Trento, Italy}, author = {Daoudi, Khalid and Fohr, Dominique and Antoine, Christophe}, booktitle = {{IEEE Automatic Speech Recognition and Understanding Workshop - ASRU'2001}}, hal_id = {inria-00107521}, hal_local_reference = {A01-R-226 || daoudi01b}, hal_version = {v1}, keywords = {speech recognition ; r{\'e}seaux bay{\'e}siens ; bayesian networks ; reocnnaissance la parole}, month = {December}, note = {Colloque avec actes et comit{\'e} de lecture. internationale.}, organization = {{IEEE}}, pages = {4 p}, pdf = {https://hal.inria.fr/inria-00107521/file/A01-R-226.pdf}, title = {{Continuous Multi-Band Speech Recognition using Bayesian Networks}}, url = {https://hal.inria.fr/inria-00107521}, year = {2001} }