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@article{196756,
        author = {Nikitha Pitla and Sneha Tangtur and BVR Bhavana and Gummadi Swetha},
        title = {MUSE AI - TRANSFORMING WORDS INTO MELODIES},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {13647-13651},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196756},
        abstract = {Muse AI- Transforming Words into Melodies is a project that showcases a system that can transform user- provided text prompts into brief musical compositions featuring synthesised vocals, background instrumentation, and dynamically generated lyrics. The pipeline starts by using a refined GPT-2 model to produce meaningful and poetic lyrics. NumPy-based tone sequencing that mimics fundamental instrumental patterns is then used to create a melodic background. A Text-to-Speech (TTS) engine is then used to turn the lyrics into audio in order to mimic vocalisation. By integrating dynamic lyric generation, music synthesis, and voice conversion into a single pipeline, this system aims to close the gap between the majority of current models that either create music or produce vocals separately. It provides an imaginative beginning point for AI-assisted music generation with a seamless audio experience. This integration shows how future systems could use developments in generative AI and voice synthesis to produce richer compositions and fully synchronised, melodic singing.},
        keywords = {AI music generation, GPT-2, dynamic lyrics, TTS, music synthesis, voice conversion, multi modal AI, Muse AI},
        month = {April},
        }