AI TrackMate: Finally, Someone Who Will Give Your Music More Than Just 'Sounds Great!'

Autor:	Jiang, Yi-Lin, Hsiung, Chia-Ho, Yeh, Yen-Tung, Chen, Lu-Rong, Chen, Bo-Yu
Rok vydání:	2024
Předmět:	Computer Science - Sound Computer Science - Human-Computer Interaction Computer Science - Machine Learning Computer Science - Multimedia Electrical Engineering and Systems Science - Audio and Speech Processing
Druh dokumentu:	Working Paper
Popis:	The rise of "bedroom producers" has democratized music creation, while challenging producers to objectively evaluate their work. To address this, we present AI TrackMate, an LLM-based music chatbot designed to provide constructive feedback on music productions. By combining LLMs' inherent musical knowledge with direct audio track analysis, AI TrackMate offers production-specific insights, distinguishing it from text-only approaches. Our framework integrates a Music Analysis Module, an LLM-Readable Music Report, and Music Production-Oriented Feedback Instruction, creating a plug-and-play, training-free system compatible with various LLMs and adaptable to future advancements. We demonstrate AI TrackMate's capabilities through an interactive web interface and present findings from a pilot study with a music producer. By bridging AI capabilities with the needs of independent producers, AI TrackMate offers on-demand analytical feedback, potentially supporting the creative process and skill development in music production. This system addresses the growing demand for objective self-assessment tools in the evolving landscape of independent music production. Comment: Accepted for the NeurIPS 2024 Creative AI Track
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2412.06617 Zobrazit plný text záznamu View this record from Arxiv