Large Vocabulary Automatic Chord Estimation with an Even Chance Training Scheme

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This paper presents a large vocabulary automatic chord estimation system implemented using a bidirectional long short-term memory recurrent neural network trained with a skewed-class-aware scheme. This scheme gives the uncommon chord types much more exposure during the training process. The evaluation results indicate that: compared with a normal training scheme, the proposed scheme can boost the weighted chord symbol recalls of some uncommon chords and significantly improve the average chord quality accuracy, at the expense of the overall weighted chord symbol recall.

本論文は、

Bidirectional LSTMをベースに、学習時に珍しいchordに多くさらすことで、非常に多クラスのchord recognitionを行なった論文？

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