Poster
in
Affinity Workshop: Global South AI
System design for Transcribing Tamil Songs to overcome language barriers
Suresh Lokiah
Keywords: [ Tamil Language ] [ machine learning ] [ Transcribing ] [ System Design ] [ Audio Analysis ]
This paper presents a transformative system designed to bridge language barriers by automatically transcribing Tamil songs into English lyrics through audio analysis. By harnessing cutting-edge audio processing and natural language translation techniques, the system enables the conversion of Tamil song vocals into meaningful English lyrics, thereby expanding cross-cultural accessibility and appreciation of Tamil music.The system's architecture involves training a sophisticated audio recognition model on a diverse dataset of Tamil songs. Through spectral analysis and linguistic pattern recognition, the model identifies vocal segments and phonetic structures, accurately capturing the essence of the original lyrics. Subsequently, a translation component powered by advanced machine translation methods converts the phonetic representations into coherent English lyrics while preserving the emotional and thematic nuances of the song.This innovation opens avenues for international audiences to engage with Tamil music in a meaningful way, transcending language barriers. Moreover, it offers a tool for language learners and enthusiasts to delve into the linguistic intricacies of Tamil songs, promoting cultural exchange and appreciation.Although challenges related to nuanced translation and cultural context arise, this paper underscores the immense potential of the proposed system to bridge linguistic gaps, foster intercultural connections, and contribute to the global music landscape. By amalgamating music, technology, and language translation, this system paves the way for a more inclusive and interconnected musical experience.