Evaluation and Comparison of Audio Chroma Feature Extraction Methods

Stein M, Schubert BM, Gruhne M, Gatzsche G, Mehnert M. Evaluation and Comparison of Audio Chroma Feature Extraction Methods. In: AES Convention 126. Audio Engineering Society; 2009. Paper 7814. Available from: https://aes.org/publications/elibrary-page/?id=15010

@inproceedings{Stein2009_15010,
  author = {Stein, Michael and Schubert, Benjamin M. and Gruhne, Matthias and Gatzsche, Gabriel and Mehnert, Markus},
  title = {{Evaluation and Comparison of Audio Chroma Feature Extraction Methods}},
  booktitle = {AES Convention 126},
  note = {Paper 7814},
  year = {2009},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=15010}
}

TY  - CPAPER
TI  - Evaluation and Comparison of Audio Chroma Feature Extraction Methods
AU  - Stein, Michael
AU  - Schubert, Benjamin M.
AU  - Gruhne, Matthias
AU  - Gatzsche, Gabriel
AU  - Mehnert, Markus
T2  - AES Convention 126
M1  - Paper 7814
PY  - 2009
DA  - 2009/05/06
UR  - https://aes.org/publications/elibrary-page/?id=15010
PB  - Audio Engineering Society
LA  - en
AB  - This paper analyzes and compares different methods for audio chroma feature extraction. The chroma feature is a descriptor, which represents the tonal content of a musical audio signal in a condensed form. Therefore chroma features can be considered as important prerequisite for high-level semantic analysis, like chord recognition or harmonic similarity estimation. A better quality of the extracted chroma feature enables much better results in these high-level tasks. In order to discover the quality of chroma features, seven different state-of-the-art chroma feature extraction methods have been implemented. Based on an audio database, containing 55 variations of triads, the output of these algorithms is critically evaluated. The best results were obtained with the Enhanced Pitch Class Profile.
ER  -