The Design and Realization of Remote Voice Control System Based on the Intelligent Home

2014 ◽  
Vol 530-531 ◽  
pp. 1112-1118
Author(s):  
Ye Fen Yang ◽  
Jun Zhang ◽  
Dong Hai Zeng
Keyword(s):  
Control System ◽  
Mobile Phone ◽  
Control Function ◽  
Voice Recognition ◽  
Security Requirements ◽  
Intelligent Home ◽  
Design Program ◽  
Wide Range ◽  
Voice Control ◽  
The Voice

A design program of remote voice control system is presented based on the intelligent home on Android mobile phone platform. Via the voice recognition of Android mobile phone, the intelligent home can have a remote voice control function by this program, which greatly improves the security requirements of the intelligent home. This system is tested and proved its real-time, effectiveness and stability. Meanwhile, it can also provide a practical reference solution for human-computer interaction, having a wide range of application.

scholarly journals Design and Fabrication of Voice Controlled Unmanned Aerial Vehicle

2016 ◽  
Vol 5 (3) ◽  
pp. 205
Author(s):  
S. Sakthi Anand ◽  
R. Mathiyazaghan
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Voice Recognition ◽  
Search And Rescue ◽  
Voice Input ◽  
Recognition Process ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
The Voice

<p class="Default">Unmanned Aerial Vehicles have gained well known attention in recent years for a numerous applications such as military, civilian surveillance operations as well as search and rescue missions. The UAVs are not controlled by professional pilots and users have less aviation experience. Therefore it seems to be purposeful to simplify the process of aircraft controlling. The objective is to design, fabricate and implement an unmanned aerial vehicle which is controlled by means of voice recognition. In the proposed system, voice commands are given to the quadcopter to control it autonomously. This system is navigated by the voice input. The control system responds to the voice input by voice recognition process and corresponding algorithms make the motors to run at specified speeds which controls the direction of the quadcopter.</p>

ROS Based Voice-Control Navigation of Intelligent Wheelchair

2015 ◽  
Vol 733 ◽  
pp. 740-744 ◽  
Author(s):  
Yi Zhang ◽  
Shi Chuan Xu
Keyword(s):  
Operating System ◽  
Control System ◽  
System Development ◽  
Powered Wheelchair ◽  
Robot Operating System ◽  
Intelligent Wheelchair ◽  
Software Packages ◽  
Voice Control ◽  
The Cost ◽  
The Voice

Compared with the traditional electric-powered wheelchair, people are paying more attention on intelligent wheelchair. While the traditional intelligent wheelchair relays on separate designed control system, it is not good for general use. In that case, ROS provides an easy to use framework for rapid system development so that the researchers can develop various software packages to meet their needs, and we can also call each other packages without considering the compatibility problems. In this paper, we present a ROS (Robot Operating System) based intelligent wheelchair with the function of voice-control navigation. Compared with the traditional navigation, the voice-control navigation is more human. Obviously, ROS increases the versatility of system and reduces the cost. In order to prove the advancement and feasibility of this developed system, some experimental results are given in the paper.

Design of Voice Control System for Smart Home Based on STM32

2015 ◽  
Vol 734 ◽  
pp. 369-374 ◽  
Author(s):  
Ping Qian ◽  
Ying Zhen Zhang ◽  
Yu Li
Keyword(s):  
Control System ◽  
Speech Recognition ◽  
Smart Home ◽  
High Performance ◽  
Practical Application ◽  
Ultra Low Power ◽  
Home Based ◽  
Voice Control ◽  
The Voice ◽  
The Internet Of Things

The application of embedded speech recognition technology in the smart home is researched, combining of the Internet of Things, the voice control system for smart home has been designed. The core processor chooses the high-performance Cortex-M4 MCU STM32F407VGT6 produced by STMicroelectronics. The system contains a hardware unit based on LD3320 for speaker-independent speech recognition. RF wireless communication uses ultra-low power chip CC1101 and GSM employ SIM900A. Real-time operating system FreeRTOS is used for multitask scheduling and the operation of household devices. The practical application verifies that this voice control system practicably can identify voice commands quickly and accurately, complete the control actions primely, has a wide application prospect.

scholarly journals Comparison of CNNs and SVM for voice control wheelchair

2020 ◽  
Vol 9 (3) ◽  
pp. 387
Author(s):  
Mohammad Shahrul Izham Sharifuddin ◽  
Sharifalillah Nordin ◽  
Azliza Mohd Ali
Keyword(s):  
Feature Extraction ◽  
Processing Time ◽  
Voice Recognition ◽  
The Other ◽  
Raspberry Pi ◽  
Intelligent Wheelchair ◽  
Voice Control ◽  
Voice Data ◽  
The Voice ◽  
Feature Extraction Technique

In this paper, we develop an intelligent wheelchair using CNNs and SVM voice recognition methods. The data is collected from Google and some of them are self-recorded. There are four types of data to be recognized which are go, left, right, and stop. Voice data are extracted using MFCC feature extraction technique. CNNs and SVM are then used to classify and recognize the voice data. The motor driver is embedded in Raspberry PI 3B+  to control the movement of the wheelchair prototype. CNNs produced higher accuracy i.e. 95.30% compared to SVM which is only 72.39%. On the other hand, SVM only took 8.21 seconds while CNNs took 250.03 seconds to execute. Therefore, CNNs produce better result because noise are filtered in the feature extraction layer before classified in the classification layer. However, CNNs took longer time due to the complexity of the networks and the less complexity implementation in SVM give shorter processing time.

scholarly journals Edge Container for Speech Recognition

Electronics ◽  
2021 ◽  
Vol 10 (19) ◽  
pp. 2420
Author(s):  
Lukáš Beňo ◽  
Rudolf Pribiš ◽  
Peter Drahoš
Keyword(s):  
Speech Recognition ◽  
Control Function ◽  
Independent Solution ◽  
Local Network ◽  
Raspberry Pi ◽  
Additional Contribution ◽  
Industrial Systems ◽  
Voice Control ◽  
Actual Speech ◽  
The Voice

Containerization has been mainly used in pure software solutions, but it is gradually finding its way into the industrial systems. This paper introduces the edge container with artificial intelligence for speech recognition, which performs the voice control function of the actuator as a part of the Human Machine Interface (HMI). This work proposes a procedure for creating voice-controlled applications with modern hardware and software resources. The created architecture integrates well-known digital technologies such as containerization, cloud, edge computing and a commercial voice processing tool. This methodology and architecture enable the actual speech recognition and the voice control on the edge device in the local network, rather than in the cloud, like the majority of recent solutions. The Linux containers are designed to run without any additional configuration and setup by the end user. A simple adaptation of voice commands via configuration file may be considered as an additional contribution of the work. The architecture was verified by experiments with running containers on different devices, such as PC, Tinker Board 2, Raspberry Pi 3 and 4. The proposed solution and the practical experiment show how a voice-controlled system can be created, easily managed and distributed to many devices around the world in a few seconds. All this can be achieved by simple downloading and running two types of ready-made containers without any complex installations. The result of this work is a proven stable (network-independent) solution with data protection and low latency.

Voice Recognition for STEM Education Using Robotics

2017 ◽  
Author(s):  
Shubo Chen ◽  
Binsen Qian ◽  
Harry Cheng
Keyword(s):  
Machine Learning ◽  
Open Source ◽  
Stem Education ◽  
Basic Concept ◽  
Voice Recognition ◽  
Voice Control ◽  
K 12 ◽  
The Voice ◽  
Recognition Technique ◽  
Machine Learning Tool

In this paper, we provide a new voice recognition framework which allows K-12 students to write programs to solve problems using voice control. The framework contains the voice recognition module SPHINX which is based on an open source machine learning tool developed by Carnegie Mellon University and a wrapper function which is written in C/C++ interpreter Ch. The wrapper function allows students to interact the module in Ch. Along with Ch programming and robotic coursework, students will get the chance to learn the basic concept of machine learning and voice recognition technique. In order to bring students attention and interest in machine learning, various tasks have been designed for students to accomplish based on the framework. The framework is also flexible for them to explore other interesting projects.

Closed Loop Fusion Technique for the Shaking Table Motion Control

2013 ◽  
Author(s):  
Keisuke Shimono ◽  
Yasutaka Tagawa
Keyword(s):  
Control System ◽  
Closed Loop ◽  
Control Function ◽  
Shaking Table ◽  
Low Frequencies ◽  
Acceleration Signal ◽  
Displacement Sensors ◽  
Wide Range ◽  
Loop Fusion ◽  
Table Motion

Shaking tables are frequently used for dynamical testing. To produce correct results, a shaking table must be able to move according to the desired acceleration signal in a wide range of frequencies. Accelerometers and displacement sensors are used for controlling input, and, in some cases, they have been used for preventing drift. However, at low frequencies, accelerometers do not always provide accurate values. We developed a shaking-table control system that uses a sensor-fusion control function. In this paper, we present the design scheme for our control system and the results of a simulation that validate it.

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