Investigating the Impact of Phonetic Cross Language Modeling on Arabic and English Speech Recognition

The lack of speech resources in the Arabic language is one of the most important obstacles facing speech researchers. Previously, we designed two Arabic and English automatic speech recognition systems (ASR) using two corpora: TIMIT for English language and West Point for Arabic language. Cross-language experiments were conducted using the two systems, and the results were determined with respect to the main class of phonemes' content in each language. As a continuation of that work, this paper analyzes the system errors of the two corpora by determining their strengths and weaknesses on system accuracies when swapping phonemes models.