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homographs
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Text to Phoneme Transcription Capable to Detect Ezafe and Homographs for Persian Speech Synthesis
, M.Sc. Thesis Sharif University of Technology ; Sameti, Hosein (Supervisor)
Abstract
In Persian language, there are some special uncertainties and complexities regarding the extraction of phonemes due to its flexible structure. In this work, we try to solve two problems caused by this issue, homographs disambiguation and Ezafe recognition in Persian text to speech systems.
In this work, two methods are presented for solving the two problems. The first one is a pattern recognition method based on Aho-Corasick algorithm that has the best performance according to the execution time. The second method is a hidden Markov model tagger based on Viterbi algorithm that uses bigram and trigram statistics. These methods are run on 10 million word corpus and the results are compared...
In this work, two methods are presented for solving the two problems. The first one is a pattern recognition method based on Aho-Corasick algorithm that has the best performance according to the execution time. The second method is a hidden Markov model tagger based on Viterbi algorithm that uses bigram and trigram statistics. These methods are run on 10 million word corpus and the results are compared...