Abstract
Searching for audio samples within a library can be a tedious
and time-consuming task. In this paper, we report on the design of a pilot automatic classification system that utilises timbral properties to automatically classify audio samples. At
this stage of the study, we have decided to work only with
orchestral audio samples. In addition, we conducted a perceptual experiment to evaluate the performance of the system
across five timbral attributes: breathiness, brightness, dullness, roughness and warmth. Promising classification results
indicate that this approach may be suitable for further work
that could also benefit some music production tasks.
| Original language | English |
|---|---|
| Number of pages | 0 |
| Journal | Proceedings of the 2nd AES Workshop on Intelligent Music Production |
| Volume | 0 |
| Issue number | 0 |
| Publication status | Published - 13 Sept 2016 |
| Event | 2nd AES Workshop on Intelligent Music Production - London Duration: 13 Sept 2016 → … |