2010 Abstracts (Summaries)

The 2010 LabROSA Chord Recognition System

Ellis, Daniel P. W.; Weller, Adrian Vivian

For the MIREX 2010 Audio Chord Extraction task, we submitted a total of four systems. Our base system is a trainable chord recognizer based on two-band chroma representations and using a Structured SVM classifier to replace the more familiar hidden Markov model. We submit two versions of this system, one which transposes all training data through all 12 possible chords to maximize the training data available for each chord (and hence improve generalization to rarely-seen chords and keys), and one which simply trains on the chords in their original transposition, leading to a smaller model and possible learning of key-specific features. We also submit two pre-trained models, based on these two frameworks, trained in-house on the 180 Beatles and 20 Queen tracks for which ground-truth chord labels have been made available.