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20182026
most citedEnd-to-End ASR for Code-switched Hindi-English Speech

6 citations · 8 across the 16 of their papers we have counts for

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eess.AS20211 cited

Automatic Speech Recognition in Sanskrit: A New Speech Corpus and Modelling Insights

Devaraja Adiga, Rishabh Kumar, Amrith Krishna +3

Automatic speech recognition (ASR) in Sanskrit is interesting, owing to the various linguistic peculiarities present in the language. The Sanskrit language is lexically productive,…

eess.AS2021

An Investigation of End-to-End Models for Robust Speech Recognition

Archiki Prasad, Preethi Jyothi, Rajbabu Velmurugan

End-to-end models for robust automatic speech recognition (ASR) have not been sufficiently well-explored in prior work. With end-to-end models, one could choose to preprocess the i…

eess.AS2020

Reduce and Reconstruct: ASR for Low-Resource Phonetic Languages

Anuj Diwan, Preethi Jyothi

This work presents a seemingly simple but effective technique to improve low-resource ASR systems for phonetic languages. By identifying sets of acoustically similar graphemes in t…

eess.AS2020

Black-box Adaptation of ASR for Accented Speech

Kartik Khandelwal, Preethi Jyothi, Abhijeet Awasthi +1

We introduce the problem of adapting a black-box, cloud-based ASR system to speech from a target accent. While leading online ASR services obtain impressive performance on main-str…

eess.AS20196 cited

End-to-End ASR for Code-switched Hindi-English Speech

Brij Mohan Lal Srivastava, Basil Abraham, Sunayana Sitaram +2

End-to-end (E2E) models have been explored for large speech corpora and have been found to match or outperform traditional pipeline-based systems in some languages. However, most p…