Automatic Piano Fingering from Partially Annotated Scores using Autoregressive Neural Networks

Author:

Ramoneda Pedro1,Jeong Dasaem2,Nakamura Eita3,Serra Xavier1,Miron Marius4

Affiliation:

1. Universitat Pompeu Fabra, Barcelona, Spain

2. Sogang University, Seoul, Republic of Korea

3. Kyoto University, Kyoto, Japan

4. Universitat Pompeu Fabra, Barcelona, CT, Spain

Funder

JSPS KAKENHI

Sogang University Research Grant

the Spanish Ministerio de Ciencia Innovacion y Universidades (MCIU)

Publisher

ACM

Reference35 articles.

1. Dzmitry Bahdanau , Kyung Hyun Cho , and Yoshua Bengio . 2015 . Neural machine translation by jointly learning to align and translate . In 3rd International Conference on Learning Representations, ICLR 2015. Dzmitry Bahdanau, Kyung Hyun Cho, and Yoshua Bengio. 2015. Neural machine translation by jointly learning to align and translate. In 3rd International Conference on Learning Representations, ICLR 2015.

2. A variable neighborhood search algorithm to generate piano fingerings for polyphonic sheet music

3. Malwine Bree and Seymour Bernstein . 1997. The Leschetizky method: A guide to fine and correct piano playing . Courier Corporation . Malwine Bree and Seymour Bernstein. 1997. The Leschetizky method: A guide to fine and correct piano playing. Courier Corporation.

4. Luca Chiantore. 2001. Historia de la técnica pianística. Alianza Madrid. Luca Chiantore. 2001. Historia de la técnica pianística. Alianza Madrid.

5. Modeling subjectiveness in emotion recognition with deep neural networks: Ensembles vs soft labels

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