IEEE ISM 2017

Reproducible research code for the article published to IEEE ISM 2017 conference:

@inproceedings{Bayle2017,
  author = {Bayle, Yann and Maršík, Ladislav and Rusek, Martin and Robine, Matthias and Hanna, Pierre and Slaninová, Kateřina and Martinovič, Jan and Pokorný, Jaroslav},
  booktitle = {Proceedings of the 19th IEEE International Symposium on Multimedia},
  link = {http://ism2017.asia.edu.tw/december-12/},
  month = {Dec.},
  title = {Kara1k: a karaoke dataset for cover song identification and singing voice analysis},
  year = {2017},
  address={Taichung, Taiwan},
  pages = {1--8}
}

Aim of the paper

• Propose a novel industrial musical database
• Cover Song Identification task on the before-mentioned database
• Singer's Gender Classification task on the before-mentioned database

Tree structure (Description of available files)

• The folder src/ contains python files necessary to reproduce our algorithm
• The folder data/ contains a file named filelist.csv that lists for each audio file:
  • the unique identifier
  • the artist name
  • the track name
  • the gender tag (female, male, females, males, mixed)
  • the language tag (en, fr, es, it, de, pt, nl)
  • a boolean indicating if features have been extracted for this audio file by:
    1. YAAFE
    2. Marsyas
    3. Essentia
    4. Vamp
    5. harmony-analyser
• The folder features/ contains features extracted by
  • bextract from Marsyas with the following command: bextract -mfcc -zcrs -ctd -rlf -flx -ws 1024 -as 898 -sv -fe.

As concerns features extracted by YAAFE, Essentia, Vamp and harmony-analyser they cannot be stored on this github repository because of their inherent size and so are available upon request for direct download. The command used for extracting features with:

• YAAFE: yaafe -r 22050 -f "mfcc: MFCC blockSize=2048 stepSize=1024" --resample -b output_dir_features input_filename
• Essentia: essentia-extractors-v2.1_beta2/streaming_extractor_music input_filename output_filename
• Vamp extracted via harmony-analyser using JNI wrapper:
  • java -jar ha-script.jar -a nnls-chroma:nnls-chroma -s .wav -t 0.07
  • java -jar ha-script.jar -a nnls-chroma:chordino-tones -s .wav -t 0.07
  • java -jar ha-script.jar -a nnls-chroma:chordino-labels -s .wav -t 0.07
  • java -jar ha-script.jar -a qm-vamp-plugins:qm-keydetector -s _wav -t 0.07
• harmony-analyser with the following commands (note that Vamp plugin analysis was first performed to extract low-level features):
  • java -jar ha-script.jar -a chord_analyser:chord_complexity_distance -s .wav -t 0.07
  • java -jar ha-script.jar -a chroma_analyser:complexity_difference -s .wav -t 0.07
  • java -jar ha-script.jar -a chord_analyser:average_chord_complexity_distance -s .wav -t 0.07
  • java -jar ha-script.jar -a chord_analyser:tps_distance -s .wav -t 0.07
  • java -jar ha-script.jar -a filters:chord_vectors -s .wav -t 0.07
  • java -jar ha-script.jar -a filters:key_vectors -s .wav -t 0.07