# Sonautic

- **Event:** [The Rejection Challenge](https://cerebralvalley.ai/e/the-rejection-challenge)
- **When:** Fri, Nov 14 at 1:00 – 6:00 PM (PST)
- **Where:** San Francisco, CA
- **Team:** [Jai Dhiman](https://cerebralvalley.ai/u/jaidhiman)
- **Gallery:** https://cerebralvalley.ai/e/the-rejection-challenge/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/the-rejection-challenge/hackathon/gallery/2

I'm building an ML piano performance evaluation system for music education, not just "did you hit the right notes," but actual musical assessment: tone quality, phrasing, dynamics, interpretation, musicality. The kind of feedback conservatory teachers give, but scalable to 225M+ musicians worldwide.

My outreach goal: Get feasibility validation and technical advice from audio ML researchers whose work I'm building on, specifically the MERT authors (the music-specific transformer I'm using) and other experts in music information retrieval, multi-modal learning, and audio ML. I'm a Berklee classical pianist who pivoted to ML engineering, and I needed to know if my architecture is feasible with limited expert labels (~300), or if I'm being naively optimistic. The stakes: I've spent 2+ weeks designing this system, translating conservatory evaluation rubrics into ML objectives. If experts say "this won't work," I need to know before investing in expensive data annotation.

---

Markdown version of https://cerebralvalley.ai/e/the-rejection-challenge/hackathon/gallery/2. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt