In Search of Automatic Rhythm Analysis Methods for Turkish and Indian Art Music
Dados Bibliográficos
| ID | 5304682 |
|---|---|
| Autores | Ajay Srinivasamurthy (0000-0002-9032-7909, Universitat Pompeu Fabra, autor correspondente), Andre Holzapfel (0000-0003-1679-6018, Universitat Pompeu Fabra), Xavier Serra (0000-0003-1395-2345, Universitat Pompeu Fabra) |
| Ano | 2014 |
| Volume | 43 |
| Fascículo | 1 |
| Páginas | 94-114 |
| Data de publicação | 2014-01-02 |
| Peer Reviewed | Sim |
| Open Access | Não |
| Tipo | ARTICLE |
| Periódico | Journal of New Music Research (JOURNAL) |
| Identificadores do periódico | ISSN: 0929-8215 • E-ISSN: 1744-5027 |
| Editora | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/09298215.2013.879902 |
| OpenAlex | W1969648747 |
| Idioma | EN |
| Citações recebidas | 4 |
| Referências citadas | 16 |
The aim of this paper is to identify and discuss various methods in computational rhythm description of Carnatic and Hindustani music of India, and Makam music of Turkey. We define and describe three relevant rhythm annotation tasks for these cultures—beat tracking, meter estimation, and downbeat detection. We then evaluate several methodologies from the state of the art in Music Information Retrieval (MIR) for these tasks, using manually annotated datasets of Turkish and Indian music. This evaluation provides insights into the nature of rhythm in these cultures and the challenges to automatic rhythm analysis. Our results indicate that the performance of evaluated approaches is not adequate for the presented tasks, and that methods that are suitable to tackle the culture specific challenges in computational analysis of rhythm need to be developed. The results from the different analysis methods enable us to identify promising directions for an appropriate exploration of rhythm analysis in Turkish, Carnatic and Hindustani music
Annotation · Data science · Linguistics · Music Information Retrieval · Musical · Natural language processing · Rhythm · Speech recognition · State of art · Turkish · Visual arts · Computer Science · Music and Audio Processing · Music Technology and Sound Studies · Neuroscience and Music Perception · Artificial Intelligence
| Obras citantes distintas | 4 |
|---|---|
| Citações por ano | 0,33 |
| Intervalo de citações | 2014 - 2025 (12) |
| Velocidade de citação | recent |
| Altamente citado | Não |
| Tipos de citação | Neutras: 3 |