Name
Abstract | ||
|---|---|---|
This paper proposes an ontology of musical performance techniques for teaching and learning support. We have attempted to support musical instrument performance from the viewpoint of knowledge-engineering. We focused on classical guitar which requires many techniques, and organized the knowledge related to guitar rendition by using a goal-oriented form of description. However, it presents several difficulties for use as a basis of knowledge-based systems such as a lack of coherence. In this study, we developed the Guitar Rendition Ontology that can serve as a guideline for classical guitar performance at learning and teaching sites. The ontology consists of 96 concepts, that describe the relationships between renditions, and 18 properties that explain the features of the concepts. We defined three properties to describe the process of action of each rendition as the core structure of guitar rendition concept: that is, action, primary-action, and conditional-action. The description form led to more appropriate expression of the action processes than the knowledge we systematized in our previous work. We significantly improved machine-readability and machine-processability by using Ontology Web Language (OWL). Moreover, we investigated some issues with the ontology in order to improve it through interviewing teachers and learners. As a result, we acquired additional information and found several problems with the domain of guitar rendition and the representation of knowledge. Furthermore, we received positive responses concerning the possibility of using the ontology on site. Finally, we described an annotation method for integrating data between the ontology and score information. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICOSC.2019.8665532 | 2019 IEEE 13th International Conference on Semantic Computing (ICSC) |
Keywords | Field | DocType |
Ontologies,Instruments,Music,Thumb,Education,Conferences | Ontology (information science),Classical guitar,Ontology,Annotation,Musical,Computer science,Interview,Musical instrument,Guitar,Artificial intelligence,Natural language processing | Conference |
ISSN | ISBN | Citations |
2325-6516 | 978-1-5386-6783-5 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nami Iino | 1 | 0 | 1.35 |
| Satoshi Nishimura | 2 | 1 | 5.14 |
| Takuichi Nishimura | 3 | 576 | 65.34 |
| Ken Fukuda | 4 | 4 | 5.60 |
| Hideaki Takeda | 5 | 179 | 25.16 |