Embedded System with Speech Recognition for Wireless Actuator Control

2008 ◽  
Author(s):  
O. Sajdl ◽  
R. Vrba
Keyword(s):  
Speech Recognition ◽  
Embedded System ◽  
Actuator Control

scholarly journals Efficient robust speech recognition with empirical mode decomposition using an FPGA chip with dual core

2020 ◽  
Vol 9 (2) ◽  
pp. 109
Author(s):  
Shing-Tai Pan ◽  
Ching-Fa Chen ◽  
Wen-Sin Tseng
Keyword(s):  
Speech Recognition ◽  
Embedded System ◽  
Empirical Mode Decomposition ◽  
Recognition System ◽  
Robust Speech Recognition ◽  
Intrinsic Mode Functions ◽  
Mode Decomposition ◽  
Original Speech ◽  
Dual Core ◽  
Computing Speed

The purpose of this paper is to accelate the computing speed of Empirical Mode Decomposition (EMD) based on multi-core embedded systems for robust speech recognition. A reconfigurable chip, Field Programmable Gate Array (FPGA), is used for the implementation of the designed system. This paper applies EMD to discompose some noised speech signals into several Intrinsic Mode Functions (IMFs). These IMFs will be combined to recover the original speech by multiplying their corresponding weights which were trained by Genetic Algorithms (GA). After applying Empirical Mode Decomposition (EMD), we obtain a cleaner speech for recognition. Due to the complexity of the computation of the EMD, a dual-core architecture of embedded system on FPGA is proposed to accelerate the computing speed of EMD for robust speech recognition. This will enhance the efficiency of embedded speech recognition system.

scholarly journals SPEECH RECOGNITION BASED EMBEDDED CONTROL SYSTEM

2014 ◽  
pp. 8-14
Author(s):  
PARVEZ HASAN ◽  
V. K. JOSEPH
Keyword(s):  
Control System ◽  
User Interface ◽  
Speech Recognition ◽  
Natural Language ◽  
Embedded System ◽  
Voice Recognition ◽  
Test Plan ◽  
Embedded Control ◽  
Novice User ◽  
Embedded Control System

The purpose of this project is to operate or control Embedded system based on voice recognition, which helps to introduce hearing as well as Natural Language (NL) interface through Speech for the Human-Embedded system interaction. One of the important goals of pursued project is to introduce suitable user interface for novice user and the test plan is to design accordingly.

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

2012 ◽  
Vol 220-223 ◽  
pp. 1986-1989 ◽  
Author(s):  
Bing Hui Fan ◽  
Peng Ji ◽  
Kai Zhou
Keyword(s):  
Neural Network ◽  
Speech Recognition ◽  
Embedded System ◽  
Real Time ◽  
Extraction Methods ◽  
Generalized Regression Neural Network ◽  
Frame Shift ◽  
Speech Control ◽  
Frame Method ◽  
Generalized Regression

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.

Speech Recognition for Endoscopic Automatic Positioning System

2012 ◽  
Vol 588-589 ◽  
pp. 1296-1299
Author(s):  
Ning Ma ◽  
Xiao Dong Chen ◽  
Ya Nan Li ◽  
Qing Yun Yin ◽  
Yi Wang ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Embedded System ◽  
Dynamic Time Warping ◽  
Recognition Rate ◽  
Positioning System ◽  
Time Warping ◽  
Embedded Platform ◽  
Speech Recognition Engine ◽  
Dynamic Time ◽  
Automatic Positioning

A novel system for minimally invasive surgery is presented in this paper. The system utilized an Endoscopic Automatic Positioner (EAP) controlled by Speech Recognition Engine to implement the clamping and dynamically positioning of the laparoscope. The motion instructions of the EAP are transformed from voice commands of specific doctor recognized by an improved algorithm named Normalized Average- Dynamic Time Warping (NA-DTW). An embedded platform based on ARM is designed to run the NA-DTW on Windows CE operating system. 1250 groups of experiments from 10 individual speakers demonstrate the performance of DTW. Compared with traditional algorithms, the enhanced algorithm improves the recognition rate from 96.6% to 99.76% and shortens the time of calculation by 51%. The results demonstrate the enhanced algorithm being effective and can satisfy the real time requirement in embedded system.

Research on Speech Recognition Robot Based on Embedded System and DSP

2014 ◽  
Vol 701-702 ◽  
pp. 341-347
Author(s):  
Xuan Gong
Keyword(s):  
Speech Recognition ◽  
Embedded System ◽  
Real Time ◽  
Model Based ◽  
High Level

This paper has a discussion and research on the design and realization of the speech recognition robot based on embedded system and DSP. The solution of embedded system and DSP has made the performance, cost, reconfigurable ability and extensible ability of the system to a high level. And the system has adapted the modified MFCC method to extract the feature of the speech and used the HMM model based on K segmented equalizing value to do the speech study and recognition. It has improved the transplanting and real-time ability of the arithmetic.

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