Conference paper

ONDEL Lucas, GODARD Pierre, BESACIER Laurent, LARSEN Elin, HASEGAWA-JOHNSON Mark, SCHARENBORG Odette, DUPOUX Emmanuel, BURGET Lukáš, YVON Francois and KHUDANPUR Sanjeev. Bayesian Models for Unit Discovery on a Very Low Resource Language. In: Proceedings of ICASSP 2018. Calgary: IEEE Signal Processing Society, 2018, pp. 5939-5943. ISBN 978-1-5386-4658-8.
Publication language:english
Original title:Bayesian Models for Unit Discovery on a Very Low Resource Language
Title (cs):Bayesovské modely pro objevování jednotek v jazycích s velmi omezenými zdroji
Proceedings:Proceedings of ICASSP 2018
Conference:IEEE International Conference on Acoustics, Speech and Signal Processing
Place:Calgary, CA
Publisher:IEEE Signal Processing Society
Acoustic Unit Discovery, Low-Resource ASR, Bayesian Model, Informative Prior.
Developing speech technologies for low-resource languages has become a very active research field over the last decade. Among others, Bayesian models have shown some promising results on artificial examples but still lack of in situ experiments. Our work applies state-of-the-art Bayesian models to unsupervised Acoustic Unit Discovery (AUD) in a real low-resource language scenario. We also show that Bayesian models can naturally integrate information from other resourceful languages by means of informative prior leading to more consistent discovered units. Finally, discovered acoustic units are used, either as the 1-best sequence or as a lattice, to perform word segmentation. Word segmentation results show that this Bayesian approach clearly outperforms a Segmental-DTW baseline on the same corpus.
   author = {Lucas Ondel and Pierre Godard and Laurent Besacier
	and Elin Larsen and Mark Hasegawa-Johnson and
	Odette Scharenborg and Emmanuel Dupoux and
	Luk{\'{a}}{\v{s}} Burget and Francois Yvon and
	Sanjeev Khudanpur},
   title = {Bayesian Models for Unit Discovery on a Very Low
	Resource Language},
   pages = {5939--5943},
   booktitle = {Proceedings of ICASSP 2018},
   year = 2018,
   location = {Calgary, CA},
   publisher = {IEEE Signal Processing Society},
   ISBN = {978-1-5386-4658-8},
   doi = {10.1109/ICASSP.2018.8461545},
   language = {english},
   url = {}

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