The core HeartMuLa model functions as an LLM-based song generator that accepts flexible, user-controllable conditions such as textual style descriptions, detailed lyrics, and reference audio inputs. It excels in multilingual support, covering languages like English, Chinese, Japanese, Korean, and Spanish, making it accessible for global creators. Specialized modes enhance its versatility: fine-grained musical attribute control lets users specify styles for individual song sections like intros, verses, choruses, and bridges using natural language prompts, while a short-music generation mode produces engaging clips ideal for background tracks in videos.
Built for both research and creative pipelines, HeartMuLa supports detailed control over elements like genre, mood, rhythm, and expressive variations, positioning it as a powerful tool for music production. Its hierarchical architecture ensures high-fidelity output even in local environments, with demonstrations showing competitive performance against proprietary systems. As an open-source solution under Apache 2.0, it fosters innovation in AI-driven music, enabling covers via Audio2Music functionality and encouraging community development for non-commercial and now commercially viable applications.
