The Implementation of Pipe Climbing Robot’s Real-Time Speech Control Based on the Generalized Regression Neural Network in Embedded System

Bing Hui Fan; Peng Ji; Kai Zhou

doi:10.4028/www.scientific.net/AMM.220-223.1986

Paper Titles

A Precoding Scheme Based Game Theory for Cooperative MIMO System
p.1969

ARM-Based Embedded Visual Processing System
p.1973

The Realization of Multiple Degree of Freedom Prosthetic Method of Random Target Location in Embeded System
p.1977

Harmonic Detection Instrument Based on Embedded System
p.1982

The Implementation of Pipe Climbing Robot’s Real-Time Speech Control Based on the Generalized Regression Neural Network in Embedded System
p.1986

Study on Parameter Determination for ECM Equivalent Circuit
p.1990

Design of Vehicle Semi-Active Suspension System Control Unit
p.1995

Influence of Machining Process on Gap-Width Detection in Pulse ECM
p.2000

A Satisfaction-Based Dynamic Bandwidth Allocation Algorithm for Heterogeneous Wireless Network
p.2004

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 220-223The Implementation of Pipe Climbing Robot’s...

The Implementation of Pipe Climbing Robot’s Real-Time Speech Control Based on the Generalized Regression Neural Network in Embedded System

Abstract:

This paper describes a speech pre-processing and feature extraction methods and described the principle of generalized regression neural network (GRNN). In order to use neural networks for speech recognition, this article uses the variable frame-shift average frame method to average the characteristic parameters of the collected voice frame, and the feasibility of the variable frame-shift average frame method in neural network input parameters normalization is verified by experiments. In this paper, according to this method, the speech recognition based on the generalized regression neural network (GRNN) successfully ported to an embedded system, and realized the pipe climbing robot’s real-time speech control.