GesRec3D: a real-time coded gesture-to-speech system with automatic segmentation and recognition thresholding using dissimilarity measures

Craven, Michael P. and Curtis, K. Mervyn (2004) GesRec3D: a real-time coded gesture-to-speech system with automatic segmentation and recognition thresholding using dissimilarity measures. In: Gesture-based communication in human-computer interaction: 5th International Gesture Workshop, GW 2003: Genova, Italy, April 2003: selected revised papers. Lecture notes in computer science (2915). Springer, Berlin, pp. 231-238. ISBN 978-3-540-21072-6

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Abstract

A complete microcomputer system is described, GesRec3D, which facilitates the data acquisition, segmentation, learning, and recognition of 3-Dimensional arm gestures, with application as a Augmentative and Alternative Communication (AAC) aid for people with motor and speech disability. The gesture data is acquired from a Polhemus electro-magnetic tracker system, with sensors attached to the finger, wrist and elbow of one arm. Coded gestures are linked to user-defined text, to be spoken by a text-to-speech engine that is integrated into the system. A segmentation method and an algorithm for classification are presented that includes acceptance/rejection thresholds based on intra-class and inter-class dissimilarity measures. Results of recognition hits, confusion misses and rejection misses are given for two experiments, involving predefined and arbitrary 3D gestures.

Item Type: Book Section
Additional Information: The original publication is available at www.springerlink.com
Keywords: gesture recognition, dissimilarity, similarity, segmentation, text-to-speech, gesture-to-speech, sign language, 3D tracking, Augmentative and Alternative Communication, AAC, human computer interaction, HCI
Schools/Departments: University of Nottingham UK Campus > Faculty of Engineering
Depositing User: Craven, Dr. Michael P.
Date Deposited: 12 Feb 2013 12:08
Last Modified: 15 Sep 2016 16:22
URI: http://eprints.nottingham.ac.uk/id/eprint/1899

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