Lexical modeling for Arabic ASR: a systematic approach

Tuka Alhanai, James Glass · 2014

Arabic has an ambiguous mapping between words and pronunciations, making it a deep orthographic system. This ambiguity can be resolved through diacritics, which if displayed, would compose 30% of characters in a text. We investigate the different dimensions of lexical modeling, covering diacritics, pronunciation rules, and acoustic based pronunciation modeling. We show the impact of explicitly modeling the different classes of diacritics (short vowels, geminates, nunnations). We further show that a phonetic lexicon, derived by applying simple pronunciation rules to diacritized words, offers the best gains in ASR performance. Finally, deriving pronunciations from acoustics, yields improvements, beyond a canonical lexicon. Index Terms: automatic speech recognition, Arabic, diacritics, pronunciation rules, language model, lexical model, joint sequence model, pronunciation mixture model.

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