BanglaIPA: Towards Robust Text-to-IPA Transcription with Contextual Rewriting in Bengali
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866908810970398720 |
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| author | Hasan, Jakir Datta, Shrestha Islam, Md Saiful Dipta, Shubhashis Roy Debnath, Ameya |
| author_facet | Hasan, Jakir Datta, Shrestha Islam, Md Saiful Dipta, Shubhashis Roy Debnath, Ameya |
| contents | Despite its widespread use, Bengali lacks a robust automated International Phonetic Alphabet (IPA) transcription system that effectively supports both standard language and regional dialectal texts. Existing approaches struggle to handle regional variations, numerical expressions, and generalize poorly to previously unseen words. To address these limitations, we propose BanglaIPA, a novel IPA generation system that integrates a character-based vocabulary with word-level alignment. The proposed system accurately handles Bengali numerals and demonstrates strong performance across regional dialects. BanglaIPA improves inference efficiency by leveraging a precomputed word-to-IPA mapping dictionary for previously observed words. The system is evaluated on the standard Bengali and six regional variations of the DUAL-IPA dataset. Experimental results show that BanglaIPA outperforms baseline IPA transcription models by 58.4-78.7% and achieves an overall mean word error rate of 11.4%, highlighting its robustness in phonetic transcription generation for the Bengali language. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_01778 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | BanglaIPA: Towards Robust Text-to-IPA Transcription with Contextual Rewriting in Bengali Hasan, Jakir Datta, Shrestha Islam, Md Saiful Dipta, Shubhashis Roy Debnath, Ameya Computation and Language Despite its widespread use, Bengali lacks a robust automated International Phonetic Alphabet (IPA) transcription system that effectively supports both standard language and regional dialectal texts. Existing approaches struggle to handle regional variations, numerical expressions, and generalize poorly to previously unseen words. To address these limitations, we propose BanglaIPA, a novel IPA generation system that integrates a character-based vocabulary with word-level alignment. The proposed system accurately handles Bengali numerals and demonstrates strong performance across regional dialects. BanglaIPA improves inference efficiency by leveraging a precomputed word-to-IPA mapping dictionary for previously observed words. The system is evaluated on the standard Bengali and six regional variations of the DUAL-IPA dataset. Experimental results show that BanglaIPA outperforms baseline IPA transcription models by 58.4-78.7% and achieves an overall mean word error rate of 11.4%, highlighting its robustness in phonetic transcription generation for the Bengali language. |
| title | BanglaIPA: Towards Robust Text-to-IPA Transcription with Contextual Rewriting in Bengali |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2601.01778 |