This work introduces new results on the modeling of early-vocal development using artificial intelligent cognitive architectures and a simulated vocal tract. The problem is addressed using intrinsically-motivated learning algorithms for autonomous sensorimotor exploration, a kind of algorithm belonging to the active learning architectures family. The artificial agent is able to autonomously select goals to explore its own sensorimotor system in regions where its competence to execute intended goals is improved. We propose to include a somatosensory system to provide a proprioceptive feedback signal to reinforce learning through the autonomous discovery of motor constraints. Constraints are represented by a somatosensory model which is unknown beforehand to the learner. Both the sensorimotor and somatosensory system are modeled using Gaussian mixture models. We argue that using an architecture which includes a somatosensory model would reduce redundancy in the sensorimotor model and drive the learning process more efficiently than algorithms taking into account only auditory feedback. The role of this proposed system is to predict whether an undesired collision within the vocal tract under a certain motor configuration is likely to occur. Thus, compromised motor configurations are rejected, guaranteeing that the agent is less prone to violate its own constraints.
CITE THIS COLLECTION
DataCiteDataCite
3 Biotech3 Biotech
3D Printing in Medicine3D Printing in Medicine
3D Research3D Research
3D-Printed Materials and Systems3D-Printed Materials and Systems
4OR4OR
AAPG BulletinAAPG Bulletin
AAPS OpenAAPS Open
AAPS PharmSciTechAAPS PharmSciTech
Abhandlungen aus dem Mathematischen Seminar der Universität HamburgAbhandlungen aus dem Mathematischen Seminar der Universität Hamburg
ABI Technik (German)ABI Technik (German)
Academic MedicineAcademic Medicine
Academic PediatricsAcademic Pediatrics
Academic PsychiatryAcademic Psychiatry
Academic QuestionsAcademic Questions
Academy of Management DiscoveriesAcademy of Management Discoveries
Academy of Management JournalAcademy of Management Journal
Academy of Management Learning and EducationAcademy of Management Learning and Education
Academy of Management PerspectivesAcademy of Management Perspectives
Academy of Management ProceedingsAcademy of Management Proceedings
Academy of Management ReviewAcademy of Management Review
Acevedo Valle, Juan Manuel; Moulin-Frier, Clément (2017). Autonomous Discovery of Motor Constraints in an Intrinsically-Motivated Vocal Learner. figshare. Collection. https://doi.org/10.6084/m9.figshare.c.3676645.v1