{'fraction_non_alphanumeric': 0.028314028314028315, 'fraction_numerical': 0.002574002574002574, 'mean_word_length': 5.53781512605042, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Phonetisaurus-based letter-to-sound transcription for Standard Arabic

Every TTS system must be able to convert graphemic strings into phonological representations for the purpose of pronouncing the input text. Phonetisaurus is a WFST (weighted finite-state transducer)-driven grapheme-to-phoneme (g2p) framework suitable for rapid development of high quality g2p systems. In this paper we present this fully data-driven technique, the preliminary investigations of the applicability of this advanced technique for automated transcription of Arabic text, and discuss the results and experiments of this method apply on a pronunciation dictionary of the Most Commonly used Arabic Words (MCAW-Dict.). Experimental results illustrate the speed and accuracy of the proposed system.