Advancing Speech Recognition in Tulu: A Research Perspective

Abstract

This research paper addresses the critical gap in Automatic Speech Recognition (ASR) technology for Tulu, a Dravidian
language spoken by over two million people in Southern India but underrepresented in digital linguistic resources. The study
proposes the development of a robust ASR system tailored to Tulu, leveraging advanced machine learning techniques such as
deep learning frameworks (DNN-HMM, hybrid models), transfer learning, and reinforcement learning