16 citations · 18 across the 8 of their papers we have counts for
5 papers · 2 filters
indic-punct: An automatic punctuation restoration and inverse text normalization framework for Indic languages
Anirudh Gupta, Neeraj Chhimwal, Ankur Dhuriya +4
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…
Effectiveness of text to speech pseudo labels for forced alignment and cross lingual pretrained models for low resource speech recognition
Anirudh Gupta, Rishabh Gaur, Ankur Dhuriya +4
In the recent years end to end (E2E) automatic speech recognition (ASR) systems have achieved promising results given sufficient resources. Even for languages where not a lot of la…
Is Word Error Rate a good evaluation metric for Speech Recognition in Indic Languages?
Priyanshi Shah, Harveen Singh Chadha, Anirudh Gupta +4
We propose a new method for the calculation of error rates in Automatic Speech Recognition (ASR). This new metric is for languages that contain half characters and where the same c…
Improving Speech Recognition for Indic Languages using Language Model
Ankur Dhuriya, Harveen Singh Chadha, Anirudh Gupta +4
We study the effect of applying a language model (LM) on the output of Automatic Speech Recognition (ASR) systems for Indic languages. We fine-tune wav2vec models for In…
Vakyansh: ASR Toolkit for Low Resource Indic languages
Harveen Singh Chadha, Anirudh Gupta, Priyanshi Shah +4
We present Vakyansh, an end to end toolkit for Speech Recognition in Indic languages. India is home to almost 121 languages and around 125 crore speakers. Yet most of the languages…