| dc.contributor.author | YCART, A | en_US |
| dc.contributor.author | BENETOS, E | en_US |
| dc.contributor.author | 19th International Society for Music Information Retrieval Conference Late-Breaking Demos Session | en_US |
| dc.date.accessioned | 2018-10-09T09:41:00Z | |
| dc.date.available | 2018-08-02 | en_US |
| dc.date.issued | 2018-09-23 | en_US |
| dc.date.submitted | 2018-08-03T16:35:59.196Z | |
| dc.identifier.uri | http://qmro.qmul.ac.uk/xmlui/handle/123456789/45985 | |
| dc.description.abstract | The MAPS dataset is the most used benchmark dataset for automatic music transcription (AMT). We propose here an updated version of the ground truth, containing precise beat, time signature, and key signature annotations. | en_US |
| dc.title | A-MAPS: Augmented MAPS Dataset with Rhythm and Key Annotations | en_US |
| dc.type | Conference Proceeding | |
| dc.rights.holder | © The Author(s) 2018 | |
| pubs.notes | No embargo | en_US |
| pubs.publication-status | Published | en_US |
| dcterms.dateAccepted | 2018-08-02 | en_US |
| qmul.funder | A Machine Learning Framework for Audio Analysis and Retrieval::Royal Academy of Engineering | en_US |
