A Novel Speech to Mouth Articulation System for Realistic Humanoid Robots

A significant ongoing issue in realistic humanoid robotics (RHRs) is inaccurate speech to mouth synchronisation. Even the most advanced robotic systems cannot authentically emulate the natural movements of the human jaw, lips and tongue during verbal communication. These visual and functional irregu...

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Bibliographic Details
Published in:Journal of intelligent & robotic systems 2021-03, Vol.101 (3), Article 54
Main Authors: Strathearn, Carl, Ma, Eunice Minhua
Format: Article
Language:English
Subjects:
Accuracy
Actuators
Aesthetic design
Articulation (speech)
Artificial Intelligence
CAD
CAD-CAM systems
Computational linguistics
Computer aided design
Computer programs
Control
Electrical Engineering
Engineering
Human engineering
Humanoid
Language processing
Machine learning
Mechanical Engineering
Mechatronics
Mouth
Natural language interfaces
Prototypes
Robotics
Robotics industry
Robots
Servomotors
Speech
Speech processing
Speech recognition
Synchronism
Tongue
Triangulation
Verbal communication
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Summary:A significant ongoing issue in realistic humanoid robotics (RHRs) is inaccurate speech to mouth synchronisation. Even the most advanced robotic systems cannot authentically emulate the natural movements of the human jaw, lips and tongue during verbal communication. These visual and functional irregularities have the potential to propagate the Uncanny Valley Effect (UVE) and reduce speech understanding in human-robot interaction (HRI). This paper outlines the development and testing of a novel Computer Aided Design (CAD) robotic mouth prototype with buccinator actuators for emulating the fluidic movements of the human mouth. The robotic mouth system incorporates a custom Machine Learning (ML) application that measures the acoustic qualities of speech synthesis (SS) and translates this data into servomotor triangulation for triggering jaw, lip and tongue positions. The objective of this study is to improve current robotic mouth design and provide engineers with a framework for increasing the authenticity, accuracy and communication capabilities of RHRs for HRI. The primary contributions of this study are the engineering of a robotic mouth prototype and the programming of a speech processing application that achieved a 79.4% syllable accuracy, 86.7% lip synchronisation accuracy and 0.1s speech to mouth articulation differential.
ISSN:0921-0296
1573-0409
DOI:10.1007/s10846-021-01332-2