Performance Control Driven Violin Timbre Model Based on Neural Networks
| Autor: | Esteban Maestre, Alfonso Perez Carrillo, Enric Guaus, Merlijn Blaauw, Jordi Bonada |
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| Rok vydání: | 2012 |
| Předmět: | |
| Zdroj: | IEEE Transactions on Audio, Speech, and Language Processing. 20:1007-1021 |
| ISSN: | 1558-7924 1558-7916 |
| DOI: | 10.1109/tasl.2011.2170970 |
| Popis: | The objective of this research is to model the relationship between actions performed by a violinist and the sound which these actions produce. Violinist actions and audio are captured during real performances by means of a newly developed sensing system from which bowing and audio descriptors are computed. A database is built with this data and used to train a generative model based on neural networks. The model is driven by a continuous sequence of bowing and fingering controls and is able to generate their corresponding sequence of spectral envelopes. The model is used for synthesis, either alone as a purely spectral model, by filling the predicted envelopes with harmonic and noisy components, or coupled with a concatenative synthesizer, where the predicted envelopes are used as time-varying filters to transform the concatenated samples. The combination of sample concatenation with the timbre model allows for the preservation of sound quality inherent in samples, while providing a high level of control. Additionally, we perform an analysis of the violinist control space and the influence of the controls on the timbre. |
| Databáze: | OpenAIRE |
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