Automatic Speech Recognition and Translation for Low Resource Languages

12Voice Cloning for Low-Resource Languages: Investigating the Prospects for Tamil

Vishnu Radhakrishnan, Aadharsh Aadhithya A., Jayanth Mohan, Visweswaran M., Jyothish Lal G.* and Premjith B.

Centre for Computational Engineering and Networking (CEN), Amrita Vishwa Vidyapeetham, Coimbatore, India

Abstract

With the emergence of artificial intelligence (AI)-powered personalized assistive tools, the surge of futuristic AI agents, and democratization of AI, techniques like voice cloning helps in blurring the line between man and machine. Although there are existing methods for voice synthesis, the task of voice cloning is challenging because the model needs to adapt to an unseen speaker with very less data. Voice cloning is a relatively new task that has not received much attention until recently. While traditional text-to-speech (TTS) systems tries to aid man-machine interaction, voice cloning takes it a step further by enabling to replicate the voice of near or dear ones. However, it is practically difficult to gather large datasets for voice cloning in domestic environments. Apart from the major limitation of data unavailability, designing a compact, mobile, and efficient model for cloning voices with only a few samples of data remains an unaddressed problem. While voice cloning models continue to improve, it remains challenging to incorporate region-specific accents and indigenous low-resource languages into machine-generated audio outputs that accurately differentiate a human ...