Pavel Klavík, A. Cristiano I. Malossi, et al.
Philos. Trans. R. Soc. A
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.
Pavel Klavík, A. Cristiano I. Malossi, et al.
Philos. Trans. R. Soc. A
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