@article {3431, title = {Identifying Violin Performers by their Expressive Trends}, journal = {Intelligent Data Analysis}, volume = {14}, year = {2010}, pages = {555-571}, publisher = {IOS Press}, abstract = {Understanding the way performers use expressive resources of a given instrument to communicate with the audience is a challenging problem in the sound and music computing field. Working directly with commercial recordings is a good opportunity for tackling this implicit knowledge and studying well-known performers. The huge amount of information to be analyzed suggests the use of automatic techniques, which have to deal with imprecise analysis and manage the information in a broader perspective. This work presents a new approach, Trend-based modeling, for identifying professional performers in commercial recordings. Concretely, starting from automatically extracted descriptors provided by state-of-the-art tools, our approach performs a qualitative analysis of the detected trends for a given set of melodic patterns. The feasibility of our approach is shown for a dataset of monophonic violin recordings from 23 well-known performers.}, url = {http://iospress.metapress.com/content/c4216v4t7l0t2576/?p=39c591e54b004b789bc1ed68a145bbad\π=3}, author = {Miguel Molina-Solana and Josep Lluis Arcos and Emilia G{\'o}mez} }