Recognition of Pen-Based Music Notation: the HOMUS dataset

被引:38
作者
Calvo-Zaragoza, Jorge [1 ]
Oncina, Jose [1 ]
机构
[1] Univ Alicante, Dept Software & Comp Syst, Alicante, Spain
来源
2014 22ND INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR) | 2014年
关键词
D O I
10.1109/ICPR.2014.524
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A profitable way of digitizing a new musical composition is by using a pen-based (online) system, in which the score is created with the sole effort of the composition itself. However, the development of such systems is still largely unexplored. Some studies have been carried out but the use of particular little datasets has led to avoid objective comparisons between different approaches. To solve this situation, this work presents the Handwritten Online Musical Symbols (HOMUS) dataset, which consists of 15200 samples of 32 types of musical symbols from 100 different musicians. Several alternatives of recognition for the two modalities - online, using the strokes drawn by the pen, and offline, using the image generated after drawing the symbol-are also presented. Some experiments are included aimed to draw main conclusions about the recognition of these data. It is expected that this work can establish a binding point in the field of recognition of online handwritten music notation and serve as a baseline for future developments.
引用
收藏
页码:3038 / 3043
页数:6
相关论文
共 27 条
[1]  
AHA DW, 1991, MACH LEARN, V6, P37, DOI 10.1007/BF00153759
[2]   KEEL: a software tool to assess evolutionary algorithms for data mining problems [J].
Alcala-Fdez, J. ;
Sanchez, L. ;
Garcia, S. ;
del Jesus, M. J. ;
Ventura, S. ;
Garrell, J. M. ;
Otero, J. ;
Romero, C. ;
Bacardit, J. ;
Rivas, V. M. ;
Fernandez, J. C. ;
Herrera, F. .
SOFT COMPUTING, 2009, 13 (03) :307-318
[3]  
[Anonymous], 1966, SOVIET PHYS DOKL
[4]  
[Anonymous], 1997, Statistical methods for speech recognition
[5]  
[Anonymous], 1 WORKSH IMPR ASS PE
[6]  
Anstice J., 1996, Proceedings Sixth Australian Conference on Computer-Human Interaction, P260, DOI 10.1109/OZCHI.1996.560019
[7]  
Azeem SA, 2012, INT C PATT RECOG, P3725
[8]   The challenge of optical music recognition [J].
Bainbridge, D ;
Bell, T .
COMPUTERS AND THE HUMANITIES, 2001, 35 (02) :95-121
[9]  
Cardoso J. S., 2012, INTJ MUTLIMEDIA INFO, P1
[10]  
Dalitz C, 2008, IEEE T PATTERN ANAL, V30, P753, DOI 10.1109/TPAM1.2007.70749