An Evaluation of Chromagram Weightings for Automatic Chord Estimation

Shi Z, Smith IJO. An Evaluation of Chromagram Weightings for Automatic Chord Estimation. In: AES Convention 137. Audio Engineering Society; 2014. Paper 9119. Available from: https://aes.org/publications/elibrary-page/?id=17442

@inproceedings{Shi2014_17442,
  author = {Shi, Zhengshan and Smith, III, Julius O.},
  title = {{An Evaluation of Chromagram Weightings for Automatic Chord Estimation}},
  booktitle = {AES Convention 137},
  note = {Paper 9119},
  year = {2014},
  month = oct,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=17442}
}

TY  - CPAPER
TI  - An Evaluation of Chromagram Weightings for Automatic Chord Estimation
AU  - Shi, Zhengshan
AU  - Smith, III, Julius O.
T2  - AES Convention 137
M1  - Paper 9119
PY  - 2014
DA  - 2014/10/06
UR  - https://aes.org/publications/elibrary-page/?id=17442
PB  - Audio Engineering Society
LA  - en
AB  - Automatic Chord Estimation (ACE) is a central task in Music Information Retrieval. Generally, audio files are parsed into chroma-based features for further processing in order to estimate the chord being played. Much work has been done to improve the estimation algorithm by means of statistical models for chroma vector transitions, but not as much attention has been given to the loudness model during the feature extraction stage. In this paper we evaluate the effect on chord-recognition accuracy due to the use of various nonlinear transformations and loudness weightings applied to the power spectrum that is "folded" to form the chromagram in which chords are detected. Nonlinear spectral transformations included square-root magnitude, magnitude, magnitude-squared (power spectrum), and dB magnitude. Weightings included A-weighted dB and Gaussian-weighted magnitude.
ER  -