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

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

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Ferreira, Flora / Erlhagen, Wolfram / Sousa, Emanuel / Louro, Luís / Bicho, E.

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. ; The work received financial support from FCT - Fundação para a Ciência e Tecnologia within the Project Scope: PEst- OE/EEI/UI0319/2014, the Research Centers for Mathematics and Algoritmi through the FCT Pluriannual Funding Program, PhD and Post-doctoral Grants (SFRH/BD/41179/2007, SFRH/BD/48529/2008 and SFRH/BPD/71874/2010, financed by POPH-QREN-Type 4.1-Advanced Training, co-funded by the European Social Fund and national funds from MEC), and Project NETT: Neural Engineering Transformative Technologies, EU-FP7 ITN (nr.289146).

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Titel :

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

Beteiligte:

Ferreira, Flora (Autor:in) / Erlhagen, Wolfram (Autor:in) / Sousa, Emanuel (Autor:in) / Louro, Luís (Autor:in) / Bicho, E. (Autor:in)

Erscheinungsdatum :

2014-10-13

DOI :

https://doi.org/10.1109/DEVLRN.2014.6982973

Medientyp :

Aufsatz (Konferenz)

Format :

Elektronische Ressource

Sprache :

Englisch

Schlagwörter :

Dynamic field model , Learning , Sequence learning , Musical sequence , Time intervals , Error correction , Working memory , Action planning , Ciências Naturais::Matemáticas , Ciências Naturais::Ciências da Computação e da Informação , Science & Technology

Klassifikation :

DDC:

629 / 780

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

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

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