Audio thumbnail generator
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Cleverthumbnailer is a command line tool that analyses songs and creates short audio thumbnails of them.


Given a full length piece of music in WAVE format (*.bwf and *.wav), cleverthumbnailer attempts to generate a short extract most representative of the track in general. It bases this decision on three factors:

  1. Segment Detection. Using the QMUL Segmenter algorithm, distinct musical sections of a piece are found. In western pop music, this algorithm detects transitions between verses, choruses, and bridges. In western classical music, segment boundaries are often found at key changes/modulations.
  2. RMS Energy profiling. The varying dynamics of a piece of music are calculated by tracking the RMS energy over the course of a piece. Sections of a piece that are loud (by default) or have a high amount of dynamic variation (--dynamic flag) are preferred for inclusion in the audio snippet generated.
  3. Applause detection. An algorithm that determines spectral centroid over time is used to detect applause within a recording. Periods of applause are avoided in the resulting audio thumbnail.



clever-thumbnailer version 0.1.0

Usage: clever-thumbnailer [options] <inputfile> <outputfile>
   -a             Enable applause detection
   -c <cropin>    Crop time from start in seconds (default 7.0)
   -C <cropout>   Crop time from end in seconds (default 7.0)
   -d             Rate sections by dynamic range rather than max loudness
   -f <fadein>    Fade-in duration in seconds (default 0.5)
   -F <fadeout>   Fade-out duration in seconds (default 2.0)
   -h             Display this help message
   -l <length>    Thumbnail length in seconds (default 30.0)
   -p <prelude>   Seconds of additional lead-in (default 10.0)
   -q             Enable quiet mode
   -v             Enable verbose mode


The code in this repository was created by Jon Tutcher in 2015 for BBC Research & Development.

QM-DSP was created by Queen Mary University of London; the segmenter module used here was developed by Mark Levy and Chris Cannam.


This project is licensed under the GNU GPLv2 license. For terms and conditions, see LICENSE.