A voting and predictive Neural Network system for use in a new artificial Larynx

Author

Russell, M.J. ; Rubin, D.M. ; Marwala, T. ; Wigdorowitz, B.

Author_Institution

Sch. of Electr. & Inf. Eng., Univ. of the Witwatersrand, Johannesburg, South Africa

fYear

2009

fDate

2-4 Dec. 2009

Firstpage

1

Lastpage

4

Abstract

A new artificial Larynx is currently under development at the University of the Witwatersrand, Johannesburg. This device uses dynamic tongue movement from a palatometer system to infer what the user is trying to say. Feature selection algorithms extract information from the palatometer data and are then used as input to a Multi-Layer Perceptron Neural Network. This paper deals with improving the success rate of the Neural Networks by using a voting system as well as a word prediction system. By using a voting system unknown non-rejected input words were correctly identified 93.5% of the time, while the system has a rejection rate of 17.36%. A set of grammar rules were developed for the word set and this improved the number of correct unknown, non-rejected words to 94.14% but increased the rejection rate to 17.74%.

Keywords

feature extraction; medical signal processing; multilayer perceptrons; speech processing; Johannesburg; University of the Witwatersrand; artificial larynx; dynamic tongue movement; feature extraction; feature selection algorithms; grammar rules; multilayer perceptron neural network; palatometer system; predictive neural network system; voting system; word prediction system; Africa; Artificial neural networks; Feature extraction; Larynx; Multi-layer neural network; Multilayer perceptrons; Neural networks; Speech synthesis; Synthesizers; Voting;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical and Pharmaceutical Engineering, 2009. ICBPE '09. International Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4244-4763-3

Electronic_ISBN

978-1-4244-4764-0

Type

conf

DOI

10.1109/ICBPE.2009.5384105

Filename

5384105