The IBM 2009 GALE Arabic speech transcription system
Brian E. D. Kingsbury, Hagen Soltau, George Saon, Stephen Mingyu Chu, Hong-Kwang Jeff Kuo, Lidia Mangu, Suman V. Ravuri, Nelson H. Morgan, Adam L. Janin · 2011
We describe the Arabic broadcast transcription system fielded by IBM in the GALE Phase 4 machine translation evaluation. Key advances over our Phase 3.5 system include improvements to context-dependent modeling in vowelized Arabic acoustic models; the use of neural-network features provided by the International Computer Science Institute; Model M language models; a neural network language model that uses syntactic and morphological features; and improvements to our system combination strategy. These advances were instrumental in achieving a word error rate of 8.9% on the Phase 4 evaluation set, and an absolute improvement of 1.6% word error rate over our 2008 system on the unsequestered Phase 3.5 evaluation data.