A Novel Speech to Mouth Articulation System for Realistic Humanoid Robots

Ma, Minhua ORCID logoORCID: https://orcid.org/0000-0001-7451-546X and Strathearn, Carl (2021) A Novel Speech to Mouth Articulation System for Realistic Humanoid Robots. Journal of Intelligent & Robotic Systems, 101. ISSN https://www.researchgate.net/publication/349648081_A_Novel_Speech_to_Mouth_Articulation_System_for_Realistic_Humanoid_Robots

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Abstract / Summary

A signi�cant 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 diferential.

Item Type: Article
ISSN: https://www.researchgate.net/publication/349648081_A_Novel_Speech_to_Mouth_Articulation_System_for_Realistic_Humanoid_Robots
Subjects: Computer Science, Information & General Works
Courses by Department: The Games Academy > Computing for Games
Depositing User: Rebecca Takeda-Frost
Date Deposited: 06 Oct 2021 15:59
Last Modified: 06 Oct 2021 15:59
URI: http://repository.falmouth.ac.uk/id/eprint/4397

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