Senthil Raja Gunaseela Boopathy


2023

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Revisiting Automatic Speech Recognition for Tamil and Hindi Connected Number Recognition
Rahul Mishra | Senthil Raja Gunaseela Boopathy | Manikandan Ravikiran | Shreyas Kulkarni | Mayurakshi Mukherjee | Ananth Ganesh | Kingshuk Banerjee
Proceedings of the Third Workshop on Speech and Language Technologies for Dravidian Languages

Automatic Speech Recognition and its applications are rising in popularity across applications with reasonable inference results. Recent state-of-the-art approaches, often employ significantly large-scale models to show high accuracy for ASR as a whole but often do not consider detailed analysis of performance across low-resource languages applications. In this preliminary work, we propose to revisit ASR in the context of Connected Number Recognition (CNR). More specifically, we (i) present a new dataset HCNR collected to understand various errors of ASR models for CNR, (ii) establish preliminary benchmark and baseline model for CNR, (iii) explore error mitigation strategies and their after-effects on CNR. In the due process, we also compare with end-to-end large scale ASR models for reference, to show its effectiveness.