Saurabh Paul, Christos Boutsidis, et al.
JMLR
We describe the Arabic broadcast transcription system fielded by IBM in the GALE Phase 5 machine translation evaluation. Key advances over our Phase 4 system include a new Bayesian Sensing HMM acoustic model; multistream neural network features; a MADA vowelized acoustic model; and the use of a variety of language model techniques with significant additive gains. These advances were instrumental in achieving a word error rate of 7.4% on the Phase 5 evaluation set, and an absolute improvement of 0.9% word error rate over our 2009 system on the unsequestered Phase 4 evaluation data. © 2011 IEEE.
Saurabh Paul, Christos Boutsidis, et al.
JMLR
Joxan Jaffar
Journal of the ACM
Cristina Cornelio, Judy Goldsmith, et al.
JAIR
Pavel Klavík, A. Cristiano I. Malossi, et al.
Philos. Trans. R. Soc. A