Learn More
The system presented here shows the feasibility of modeling the knowledge involved in a complex musical activity by integrating sub-symbolic and symbolic processes. This research focuses on the question of whether there is any advantage in integrating a neural network together with a distributed artificial intelligence approach within the music domain. The(More)
We describe a sequential neural network for harmonizing melodies in real-time. The network models aspects of human cognition and can be used as the basis for building an interactive system that automatically generates accompaniment for simple melodies in live performance situations. The net learns relations between important notes of the melody and their(More)
There are musical activities in which we are faced with symbolic and sub-symbolic processes. This research focuses on the question whether there is any advantage in integrating a neural network together with a distributed artiicial intelligence approach in the musical domain. In this work, we present a new approach for composing and analyzing polyphonic(More)
We describe a series of experiments using sequential neural networks to model the effect of contextual bias in music cognition. The model quantifies the strength and specificity of a virtual listener’s expectations while listening to functional tonal harmonic chord sequences. The network integrates pools of duple and triple metric units with pitch class(More)
Wc describe a hybrid system to model context formulation and resulting expectations created by a listener while attending to tonal music. The model is hybrid in that we use modular sub-networks to simulate the distinct yet mutually influential schemas involved in constructing expectations for sequential events and the temporal cyclical grid that creates(More)
We built a system that allows musical performers (and listeners) who wish to play together to organize into multiple session groups. The users interact in real time over the network, and may dynamically join or leave a session group. The players contribute to the session by playing on their MIDI controllers, using General MIDI protocol. We assume a totally(More)
We describe a model of music cognition based on uctuations in the degree of realized expectation (DRE) in which we employ a neural network which receives representations of standard and anomalous chord progressions derived from opening periods of piano sonatas by Mozart and Haydn. In order to account for essential metric information we incorporate(More)