Analyzing Chroma Feature Types for Automated Chord Recognition

Jiang N, Grosche P, Konz V, Müller M. Analyzing Chroma Feature Types for Automated Chord Recognition. In: AES Conference: 42nd International Conference: Semantic Audio. Audio Engineering Society; 2011. Paper 7-2. Available from: https://aes.org/publications/elibrary-page/?id=15943

@inproceedings{Jiang2011_15943,
  author = {Jiang, Nanzhu and Grosche, Peter and Konz, Verena and Müller, Meinard},
  title = {{Analyzing Chroma Feature Types for Automated Chord Recognition}},
  booktitle = {AES Conference: 42nd International Conference: Semantic Audio},
  note = {Paper 7-2},
  year = {2011},
  month = jul,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=15943}
}

TY  - CPAPER
TI  - Analyzing Chroma Feature Types for Automated Chord Recognition
AU  - Jiang, Nanzhu
AU  - Grosche, Peter
AU  - Konz, Verena
AU  - Müller, Meinard
T2  - AES Conference: 42nd International Conference: Semantic Audio
M1  - Paper 7-2
PY  - 2011
DA  - 2011/07/06
UR  - https://aes.org/publications/elibrary-page/?id=15943
PB  - Audio Engineering Society
LA  - en
AB  - The computer-based harmonic analysis of music recordings with the goal to automatically extract chord labels directly from the given audio material constitutes a major task in music information retrieval. In most automated chord recognition procedures, the given music recording is first converted into a sequence of chroma-based audio features and then pattern matching techniques are applied to map the chroma features to chord labels. In this paper, we analyze the role of the feature extraction step within the recognition pipeline of various chord recognition procedures based on template matching strategies and hidden Markov models. In particular, we report on numerous experiments which show how the various procedures depend on the type of the underlying chroma feature as well as on parameters that control temporal and spectral aspects.
ER  -