Paper ID: 2203.16825

indic-punct: An automatic punctuation restoration and inverse text normalization framework for Indic languages

Anirudh Gupta, Neeraj Chhimwal, Ankur Dhuriya, Rishabh Gaur, Priyanshi Shah, Harveen Singh Chadha, Vivek Raghavan

Automatic Speech Recognition (ASR) generates text which is most of the times devoid of any punctuation. Absence of punctuation is text can affect readability. Also, down stream NLP tasks such as sentiment analysis, machine translation, greatly benefit by having punctuation and sentence boundary information. We present an approach for automatic punctuation of text using a pretrained IndicBERT model. Inverse text normalization is done by hand writing weighted finite state transducer (WFST) grammars. We have developed this tool for 11 Indic languages namely Hindi, Tamil, Telugu, Kannada, Gujarati, Marathi, Odia, Bengali, Assamese, Malayalam and Punjabi. All code and data is publicly. available

Submitted: Mar 31, 2022