MUSIC RECOGNITION

Supplementary files for the paper:

Pitch Detection Enhancement Employing Music Prediction

Marek Szczerba, Andrzej Czyżewski
 

Files are in Mathematica 3.0 format. Free MathReader can be downloaded from the Wolfram Research site.

Mathematica notebooks

Fundamental frequency detection using autocorrelation method [autocorr.nb]
Comb-filter method [comb.nb]
Meddis-Hewitt method [meddis.nb]
Cepstral method [cepstral.nb]
Fundamental frequency detection using AMDF [amdf.nb]
Beauchamp detector [beauchamp.nb]
Pitch tracking based on McAulay-Quatieri method [mcaq.nb]
Fundamental frequency detection based on envelope analysis [envelope.nb]
Schroeder's histogram [histogram.nb]
Fundamental frequency detection based on paralell processing [paralell.nb]
Spectral compression [spectrcomp.nb]
Histogram in frequency domain [spectrdiv.nb]
Zero-crossing threshold methods - TABE [TABE.nb]
Zero-crossing threshold methods - TTABE [TTABE.nb]
Zero-crossing threshold methods - ZXABE [ZXABE.nb]
Pitch tracking based on short-time processing [pitchtrack.nb]
All notebooks, zipped (2MB) [notebooks.zip]
 

Data files

Data files - autok.dat, autoc_0.data, autoc_0.8.data (zipped, 3.66MB) [datafiles.zip]
 

WAV files

1akord.wav
1drawbar.wav
1fuzz.wav
1organ.wav
1piano.wav
1square.wav
1trumpet.wav
filtered.wav
oboe1.wav
speech.wav
testmq.wav
 

MIDI files

1akord.mid
1drawbar.mid
1guit.mid
1oboe.mid
1organ.mid
1piano.mid
1rockorg.mid
1saw.mid
1sbrass.mid
1square.mid
1trump.mid
1violin.mid