The reviewed record of science sign in
Pith

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

Reviewed by Pithpith:K2FJF4NUopen to challenge →

classification cs.CL
keywords punctuationtextautomaticindicinverselanguagesnormalizationabsence
0
0 comments X
read the original abstract

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

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. BhashaSutra: A Task-Centric Unified Survey of Indian NLP Datasets, Corpora, and Resources

    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.