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Research prototype built during my internship at the Centre for Advanced Research Studies, GUNI.
A full end-to-end hybrid pipeline: Transformer-based symbolic planning generates MIDI structure, a Mel-Spectrogram Diffusion U-Net renders audio, and Direct Preference Optimization (DPO) aligns outputs to human preferences — all from a single text prompt.
Stack: Python · PyTorch · Transformers · Diffusion Models · DPO · FluidSynth
This is research-grade work, not a tutorial clone. Architecture decisions, compute tradeoffs, and qualitative evaluation were all done hands-on. Research paper in progress.
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