Automatic Music Transcription Supporting Different Instruments
Bibliographic Data
| ID | 14872115 |
|---|---|
| Authors | Ivan Bruno (University of Florence, corresponding author), Paolo Nesi (0000-0003-1044-3107, University of Florence) |
| Year | 2005 |
| Volume | 34 |
| Issue | 2 |
| Pages | 139-149 |
| Publication date | 2005-06-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of New Music Research (JOURNAL) |
| Journal identifiers | ISSN: 0929-8215 • E-ISSN: 1744-5027 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/09298210500148652 |
| OpenAlex | W2017391310 |
| Language | EN |
| References cited | 13 |
Automatic music recognition from an audio performance is a key challenge for coding music in Western music notation in the digital world. This problem has been addressed in several ways, obtaining suitable results when a single specific instrument and monophonic music are processed. The development of a system for automatic music transcription that is able to cope with different music instruments is the aim of this article. Experimental results have shown that for monophonic pieces, recognition is quite viable and the process can be parameterized to realize a music-independent recognition tool and process. © 2005 Taylor and Francis
Arithmetic · Audio signal · Digital audio · Multimedia · Music education · Musical · Musical composition · Musical notation · Notation · Parameterized complexity · Pop music automation · Programming language · Speech coding · Speech recognition · Visual arts · Computer Science · Mathematics · Music and Audio Processing · Music Technology and Sound Studies · Psychology · Speech and Audio Processing
| Highly cited | No |
|---|