The IBM 2006 Gale Arabic ASR System

This paper describes the advances made in IBM´s Arabic broadcast news transcription system which was fielded in the 2006 GALE ASR and machine translation evaluation. These advances were instrumental in lowering the word error rate by 42% relative over the course of one year and include: training on additional LDC data, large-scale discriminative training on 1800 hours of unsupervised data, automatic vowelization using a flat-start approach, use of a large vocabulary with 617K words and 2 million pronunciations and lastly, a system architecture based on cross-adaptation between unvowelized and vowelized acoustic models.