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.

翻译：尽管孟加拉语应用广泛，但目前仍缺乏能够有效支持标准语言及区域方言文本的鲁棒自动化国际音标（IPA）转录系统。现有方法在处理区域变体、数字表达时存在困难，且对未见过词汇的泛化能力较差。为突破这些局限，我们提出BanglaIPA——一种融合字符级词汇与词级对齐的新型IPA生成系统。该系统能准确处理孟加拉语数字，并在各区域方言上表现出强劲性能。BanglaIPA通过利用预计算的已见词到IPA映射词典来提升推理效率。我们在标准孟加拉语及DUAL-IPA数据集的六种区域变体上对该系统进行评估。实验结果表明，BanglaIPA较基线IPA转录模型性能提升58.4-78.7%，整体平均词错误率低至11.4%，彰显了其在孟加拉语语音转录生成方面的鲁棒性。