/-Fingerprint-Shazam-like

Fingerprinting is basically to identify a signal based on a short sample for it which usually has its intrinsic features and thus these intrinsic features can be used to identify the different varieties or flavors of the signal. Several applications can be directly spotted for such technique. For example: Music industry: Identify a song, a singer voice, a tune. Medical diagnosis: identify arrhythmia types in ECG signals.

Primary LanguageJupyter NotebookMIT LicenseMIT

Fingerprint-Shazam_DSP2022 (pyqt5)

description

-is basically to identify a signal based on a short sample for it which usually has its intrinsic features and thus these intrinsic features penalized.

Features

  • used to get all percentage for all musics in the database
  • pop up spectrogram for this signal
  • music features used 1- mfcc:MFCC coefficients are used to represent the shape of the spectrum. 2- chroma:Compute a chromagram from a waveform or power spectrogram. 3- melspectrogram : spectrum of intensity of sound
  • mixer of 2 songs with slider on uploading two musics

python_packages :

  • PyQt5.QtWidgets
  • PyQt5.uic
  • operator
  • imagehash
  • librosa
  • PIL

screenshots:

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