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

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arxiv 2203.16825 v1 pith:K2FJF4NU submitted 2022-03-31 cs.CL

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

classification cs.CL
keywords punctuationtextautomaticindicinverselanguagesnormalizationabsence
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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

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    cs.CL 2026-04 unverdicted novelty 7.0

    A unified survey that consolidates Indian NLP resources by task, language, domain, and modality while identifying gaps in coverage and generalization.