https://github.com/richard-hartmann/tuner

piano tuner (general pitch detection) in Python
https://github.com/richard-hartmann/tuner

audio-processing frequency-analysis piano-utils pitch-detection pitch-estimation python3 tuner

Last synced: 6 months ago
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piano tuner (general pitch detection) in Python

• Host: GitHub
• URL: https://github.com/richard-hartmann/tuner
• Owner: richard-hartmann
• License: gpl-3.0
• Created: 2022-11-10T11:53:27.000Z (almost 3 years ago)
• Default Branch: master
• Last Pushed: 2022-11-25T10:22:13.000Z (almost 3 years ago)
• Last Synced: 2025-04-13T07:59:55.907Z (6 months ago)
• Topics: audio-processing, frequency-analysis, piano-utils, pitch-detection, pitch-estimation, python3, tuner
• Language: Jupyter Notebook
• Homepage:
• Size: 1.56 MB
• Stars: 0
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Tuner

by Richard Hartmann

Tuner - frequency analysis of the microphone input suitable to tune instruments.

![image gui](doc/gui.png "tuner-App")

## Install and Run

if you have not, install `poetry`, dependency management and packaging in Python.  

Use `poetry install` to install dependencies.

Run the app by `poetry run python start_tuner.py`

## Usage

0) Make sure the desired microphone is selected.

   If you do not want to tune to a at 440Hz, change the value

1) Select the key you want to tune to. Use the 'next' and 'prev' to see how the

   inputs 'key' and 'level' work. It also shows the target frequency of that key.

2) Play a tone and tune such that the relative difference (upper right panel) 

   is well below 1% (0.01) for some time. 

   You can use the mouse (drag and scroll) to adjust the axes.

## License

GNU General Public License v3.0

## Donation

If you like the tuner-App, feel free to 

[donate with PayPal](https://www.paypal.com/donate/?hosted_button_id=E8LH2WMYGQCGG).

If you don't like PayPal, contact me at richard_hartmann(at)gmx.ⅾⅇ.

## Basic Idea of the Algorithm

1) Perform Fourier integral (finite integral over several oscillations 

   of the recoded microphone signal) for frequencies in the vicinity of a given

   target frequency Ω, and multiples of that (higher harmonics contributions).

2) Plot such spectra and shift the frequency axis by -nΩ 

   (different shift for each higher harmonic!).

   In that way, if the base frequency of the recoded signal ω1 

   is resonant with Ω, all maxima should align at ω-nΩ = 0.

   In practice the maxima of the spectra vary much over time, 

   so their alignment is not well suited to judge the resonance, 

   i.e. the tuning to the target frequency Ω.

   (upper left plot)

3) Use the amplitude and phase information from the Fourier integral as

   initial condition to fit a harmonic model signal with base frequency 

   ω1 and its higher harmonics nω1 to the 

   recoded input. 

   (lower plot)

4) Show the relative difference of the optimal value ω1 with 

   respect to the target frequency Ω.

   Keep track of its value over some time.

   Record no value if the least square fitting does not converge sufficiently fast.

   (upper right plot)

## Acknowledgements

As of the great collection of numeric routines provided by 

[numpy](https://numpy.org/) putting the algorithm in place was straight forward.

The plotting was made possible using [Qt](https://www.qt.io/) wrapped to 

[Python](https://www.python.org/) via [pyqtgraph](https://www.pyqtgraph.org/).

Thanks!