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>Except that a single C note (especially on stringed instruments) may have many harmonics that also look like a C chord. The problem isn't straightforward. It'
by jdietrich 7y ago
>Except that a single C note (especially on stringed instruments) may have many harmonics that also look like a C chord. The problem isn't straightforward.
It's not terribly difficult either. For plucked or struck strings, you can rely on the inharmonicity of the overtones to distinguish fundamentals from harmonics. Ensemble bowed strings are more tricky because the overtones are mode-locked, but we can rely on variance between individual players in both the time and frequency domain.
Polyphonic pitch detection is a bread-and-butter feature in many commercial music technology products and the industry is many years ahead of academia; I have absolutely no doubt that you'd be able to buy automatic transcription software right now if the market was big enough to justify the R&D spend.
- vnorilo 7y agoCTO at previous job was responsible for one of the better heuristic algorithms from the era before ML took over and our product dealt with this problem. I'm inclined to disagree with your assessment. Transcription is to polyphonic pitch detection what machine translation is to OCR. We are okay at the latter, which is what folks like Celemony make their living in. We still suck terribly at the former. The last 20% will be fiendishly hard, as it depends on a mountain of cultural knowledge. A tool to help amateur transcribers to get ~70% of the way is probably within reach of current tech.
- jacquesm 7y agoYes, it is. And that 70% you can reach fairly easily, after that it gets really hard to make progress.