Software Description: MuseBook Tuner is real-time pitch detection tuning software. Getting musical sound input from a conventional microphone, MuseBook Tuner shows the tuning status of an instrument and displays the performed note on a stave and piano keyboard at the same time.
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Related:Pitch Algorithm Detection - Edge Detection Algorithm - Mermaid Melody Pitch Pitch - Pitch Pitch - Dj Audio Pitch
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Pitch detection algorithms
Autocorrelation-based C++ pitch detection algorithms with O(nlogn) or lower running time:
- McLeod pitch method - 2005 paper - visualization
- YIN(-FFT) - 2002 paper - visualization
- Probabilistic YIN - 2014 paper
- Probabilistic MPM - my own invention
- SWIPE' - 2007 paper - transliterated to C++ from kylebgorman's C implementation*
*: SWIPE' appears to be O(n) but with an enormous constant factor. The implementation complexity is much higher than MPM and YIN and it brings in additional dependencies (BLAS + LAPACK).
Suggested usage of this library can be seen in the utility wav_analyzer, which divides a wav file into chunks of 0.01s and checks the pitch of each chunk. Sample output of wav_analyzer:
Degraded audio tests
All testing files are here - the progressive degradations are described by the respective numbered JSON file, generated using audio-degradation-toolbox. The original clip is a Viola playing E3 from the University of Iowa MIS.
The results come from parsing the output of wav_analyzer to count how many 0.1s slices of the input clip were in the ballpark of the expected value of 164.81 - I considered anything 160-169 to be acceptable:
Degradation level | MPM # correct | YIN # correct | SWIPE' # correct |
---|---|---|---|
0 | 26 | 22 | 5 |
1 | 23 | 21 | 13 |
2 | 19 | 21 | 9 |
3 | 18 | 19 | 7 |
4 | 19 | 19 | 6 |
5 | 18 | 19 | 5 |
Build and install
Using this project should be as easy as
make && sudo make install
on Linux with a modern GCC - I don't officially support other platforms.This project depends on ffts, BLAS/LAPACK, and mlpack. To run the tests, you need googletest, and run
make -C test/ && ./test/test
. To run the bench, you need google benchmark, and run make -C test/ bench && ./test/bench
.Build and install pitch_detection, run the tests, and build the sample application, wav_analyzer:
Usage
Read the header and sample wav_analyzer.
The namespaces are
pitch
and pitch_alloc
. The functions and classes are templated for <double>
and <float>
support.The
pitch
namespace functions perform automatic buffer allocation, while pitch_alloc::{Yin, Mpm}
give you a reusable object (useful for computing pitch for multiple uniformly-sized buffers):