Name
Abstract | ||
|---|---|---|
In this paper we present first results on musical instrument classification using an HMM based recognizer. The final goal of our work is to automatically evaluate instruments and to classify them according to their characteristics. The first step in this direction was to train a system that is able to recognize a particular instrument among others of the same kind (e.g. guitars). The recognition is based on solo music pieces played on the instrument under various conditions. For this purpose a database was designed and is currently being recorded that comprises four instrument types: classi- cal guitar, violin, trumpet and clarinet. We briefly describe the classifier and give first experimental results on the clas- sification of acoustic guitars. |
Year | Venue | Keywords |
|---|---|---|
2006 | ISMIR 2013 | multimedia content description,mu- sic content processing,automatic musical instrument recognition,hidden markov model |
Field | DocType | Citations |
Classical guitar,Computer science,Musical instrument classification,Violin,Speech recognition,Guitar,Artificial intelligence,Classifier (linguistics),Hidden Markov model,Machine learning | Conference | 4 |
PageRank | References | Authors |
0.64 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matthias Eichner | 1 | 61 | 8.74 |
| Matthias Wolff | 2 | 68 | 14.17 |
| Rüdiger Hoffmann | 3 | 105 | 26.70 |