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Approaches:
- Spectral peak picking / Vocoder / HPS (still insufficient spectral resolution)
- Sliding Q-Transform + "Fast, Accurate Freq 5361 uency Estimators" + HPS (better spectral resolution)
- Cepstral analysis (e.g. combined with formant extraction)
- Autocorrelation / YIN (e.g. via separate CPU task)
- F0 detection via regression analysis
- CREPE via Torch
See also:
- Comparison of Pitch Trackers for Real-Time Guitar Effects
- Real-time Pitch Tracking in Audio Signals with the Extended Complex Kalman Filter + orchidas/Pitch-Tracking
- sevagh/pitch-detection
- Traditional Machine Learning for Pitch Detection
- Fast, Accurate Frequency Estimators
TODO:
- https://dsp.stackexchange.com/questions/27029/fast-pitch-recognition
- https://dsp.stackexchange.com/questions/29962/how-to-deal-with-low-fundamental-when-using-amdf-for-pitch-extraction
- https://dsp.stackexchange.com/questions/22067/what-is-an-amdf
- https://stackoverflow.com/questions/973370/fast-average-square-difference-function
- https://stackoverflow.com/questions/3949324/calculate-autocorrelation-using-fft-in-matlab
- https://stackoverflow.com/questions/4583950/cepstral-analysis-for-pitch-detection
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