Learning a musical sequence by observation: A robotics implementation of a dynamic neural field model

• Type: Article in International Conference Proceedings Book
• Date: 2014

Authors

Ferreira, F (Author) Other; Erlhagen, W (Author) Other; Sousa, E (Author) Other; Louro, L (Author) Other; Bicho, E (Author) Other

Conference proceedings International

Title: FOUTH JOINT IEEE INTERNATIONAL CONFERENCES ON DEVELOPMENT AND LEARNING AND EPIGENETIC ROBOTICS (IEEE ICDL-EPIROB 2014)

Pages: 157-162

4th Joint IEEE International Conferences on Development and Learning and Epigenetic Robotics (IEEE ICDL-Epirob)

Genoa, ITALY, OCT 13-16, 2014

Indexing

ISI Web of Knowledge - 9 Citations

Scopus - 10 Citations

Other information

Authenticus ID: P-00A-A9D

DOI: 10.1109/devlrn.2014.6982973

Abstract (EN): We tested in a robotics experiment a dynamic neural field model for learning a precisely timed musical sequence. Based on neuro-plausible processing mechanisms, the model implements the idea that order and relative timing of events are stored in an integrated representation whereas the onset of sequence production is controlled by a separate process. Dynamic neural fields provide a rigorous theoretical framework to analyze and implement the necessary neural computations that bridge gaps between sensation and action in order to mediate working memory, action planing, and decision making. The robot first memorizes a short musical sequence performed by a human teacher by watching color coded keys on a screen, and then tries to execute the piece of music on a keyboard from memory without any external cues. The experimental results show that the robot is able to correct in very few demonstration-execution cycles initial sequencing and timing errors.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6