Context-dependent pronunciation modeling for Iraqi ASR

In this paper, we introduce a novel pronunciation modeling technique that in contrast to existing techniques uses word context information. This context-dependent pronunciation modeling is designed to overcome the challenges posed by absence of diacritics in transcripts for training acoustic models for Arabic dialects. To demonstrate the efficacy of the proposed pronunciation modeling, we present experimental results with both manually created and automatically generated vowelized lexicons on the DARPA TRANSTAC colloquial Iraqi corpus.