Multi-Module G2P Converter for Persian Focusing on Relations between Words

• URL: http://arxiv.org/abs/2208.01371v1
• Date: Tue, 2 Aug 2022 11:33:48 GMT
• Title: Multi-Module G2P Converter for Persian Focusing on Relations between Words
• Authors: Mahdi Rezaei, Negar Nayeri, Saeed Farzi, Hossein Sameti
• Abstract summary: Our proposed multi- module G2P system outperforms our end-to-end systems in terms of accuracy and speed. The system is sequence-level rather than word-level, which allows it to effectively capture the unwritten relations between words.
• Score: 1.3764085113103217
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we investigate the application of end-to-end and multi-module frameworks for G2P conversion for the Persian language. The results demonstrate that our proposed multi-module G2P system outperforms our end-to-end systems in terms of accuracy and speed. The system consists of a pronunciation dictionary as our look-up table, along with separate models to handle homographs, OOVs and ezafe in Persian created using GRU and Transformer architectures. The system is sequence-level rather than word-level, which allows it to effectively capture the unwritten relations between words (cross-word information) necessary for homograph disambiguation and ezafe recognition without the need for any pre-processing. After evaluation, our system achieved a 94.48% word-level accuracy, outperforming the previous G2P systems for Persian.

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