Analysis of Rachmaninoff's Piano Performances Using Inductive Logic Programming (Extended Abstract)
ECML '95 Proceedings of the 8th European Conference on Machine Learning
In search of the Horowitz factor
AI Magazine
Rencon 2004: Turing test for musical expression
NIME '04 Proceedings of the 2004 conference on New interfaces for musical expression
Visualizing Expressive Performance in Tempo-Loudness Space
Computer Music Journal
Generating Musical Performances with Director Musices
Computer Music Journal
Emotional Coloring of Computer-Controlled Music Performances
Computer Music Journal
Estimation of Parameters in Rule Systems for Expressive Rendering of Musical Performance
Computer Music Journal
Music and Probability
Using string kernels to identify famous performers from their playing style
Intelligent Data Analysis
Inmamusys: Intelligent multiagent music system
Expert Systems with Applications: An International Journal
Automatic identification of music performers with learning ensembles
Artificial Intelligence
Performance-Based Interpreter Identification in Saxophone Audio Recordings
IEEE Transactions on Circuits and Systems for Video Technology
| Hi-index | 12.05 |
Musical expressivity can be defined as the deviation from a musical standard when a score is performed by a musician. This deviation is made in terms of intrinsic note attributes like pitch, timbre, timing and dynamics. The advances in computational power capabilities and digital sound synthesis have allowed real-time control of synthesized sounds. Expressive control becomes then an area of great interest in the sound and music computing field. Musical expressivity can be approached from different perspectives. One approach is the musicological analysis of music and the study of the different stylistic schools. This approach provides a valuable understanding about musical expressivity. Another perspective is the computational modelling of music performance by means of automatic analysis of recordings. It is known that music performance is a complex activity that involves complementary aspects from other disciplines such as psychology and acoustics. It requires creativity and eventually, some manual abilities, being a hard task even for humans. Therefore, using machines appears as a very interesting and fascinating issue. In this paper, we present an overall view of the works many researchers have done so far in the field of expressive music performance, with special attention to the computational approach.