Approach to the voice control of IoT objects in “smart house” systems

2021 ◽  
pp. 37-50
Author(s):  
Igor Shostak ◽  
Vitalina Babenko ◽  
Mariia Danova ◽  
Olena Feoktystova
Keyword(s):  
Voice Control ◽  
Smart House ◽  
The Voice

A Detection System of Location and Direction Angle by a RF Tag Reader Using a Rotary Antenna

2008 ◽  
Vol 20 (1) ◽  
pp. 189-195 ◽  
Author(s):  
Takashi Asakawa ◽  
◽  
Kazue Nishihara ◽  
Tadashi Yoshidome ◽  
Keyword(s):  
Turning Point ◽  
Detection System ◽  
Automatic Correction ◽  
Electric Wheelchair ◽  
Direction Angle ◽  
Voice Control ◽  
Moving Direction ◽  
Rf Tags ◽  
The Voice ◽  
Voice Instruction

This paper describes the method of presuming the angle of moving direction of an electric wheelchair by reading information of RF tags put on a floor using a rotary antenna, which is fixed underneath the wheelchair, revolving constantly above RF tags of the floor at a turning point. Our primary intention is to make a detection system of direction angle using RF tags for a voice controlled electric wheelchair. The voice instruction cannot give smooth nor detailed controls with ease unlike the joystick control. Because the voice control system can use only a few discrete instruction words. Thereby to assist smooth indoor motion, we proposed here a new method of automatic correction of the direction angle measured by the above rotary antenna and RF tags. We demonstrated experimentally to detect and correct the angle of moving direction when the wheelchair passes over the turning point, which was found to give accurate orientations.This paper is the full translation from the transactions of JSME Vol.73, No.729.

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.

scholarly journals IoT Based Voice Controlled Multitasking System for Home

2019 ◽  
Vol 9 (1) ◽  
pp. 4265-4268
Keyword(s):  
Internet Of Things ◽  
Smart Home ◽  
Raspberry Pi ◽  
Family Unit ◽  
Human Voice ◽  
The Family ◽  
Voice Control ◽  
The Voice ◽  
Dedicated Hardware

Internet of Things is a rising innovation that makes our world more astute. In recent years, there has been immense development in the realm of insightful gadgets for home mechanization. Such contraptions are planned so as to facilitate communication among individuals and everyday home obligations. This paper exhibits a voice-controlled smart home with multi-functions using ESP32 as the wireless choice. Voice control (using human voice to control any load like light, fan, ac, geyser, motor etc.). The voice-commands are recognized by a dedicated hardware module and the recognized data is sent to database using ESP32. On the accepting unit, raspberry pi peruses the information from the database and deciphers the directions verbally expressed by the client and controls the family unit apparatuses.

scholarly journals Moderate evidence for a Lombard effect in a phylogenetically basal primate

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2328 ◽  
Author(s):  
Christian Schopf ◽  
Sabine Schmidt ◽  
Elke Zimmermann
Keyword(s):  
Auditory Feedback ◽  
Background Noise ◽  
Vocal Communication ◽  
Lombard Effect ◽  
Voice Control ◽  
Mouse Lemurs ◽  
System Properties ◽  
First Time ◽  
The Voice ◽  
Grey Mouse Lemur

When exposed to enhanced background noise, humans avoid signal masking by increasing the amplitude of the voice, a phenomenon termed the Lombard effect. This auditory feedback-mediated voice control has also been found in monkeys, bats, cetaceans, fish and some frogs and birds. We studied the Lombard effect for the first time in a phylogenetically basal primate, the grey mouse lemur,Microcebus murinus. When background noise was increased, mouse lemurs were able to raise the amplitude of the voice, comparable to monkeys, but they did not show this effect consistently across context/individuals. The Lombard effect, even if representing a generic vocal communication system property of mammals, may thus be affected by more complex mechanisms. The present findings emphasize an effect of context, and individual, and the need for further standardized approaches to disentangle the multiple system properties of mammalian vocal communication, important for understanding the evolution of the unique human faculty of speech and language.

The Design of a Voice Control System for Smart House

2014 ◽  
Vol 644-650 ◽  
pp. 741-745
Author(s):  
Wei Zhang ◽  
Yu Huai Liu
Keyword(s):  
Control System ◽  
Power Consumption ◽  
Low Power ◽  
Wireless Network ◽  
Sensor Node ◽  
Low Cost ◽  
Low Power Consumption ◽  
Zigbee Technology ◽  
Voice Control ◽  
Smart House

A method to design a voice control system for smart house is proposed and implemented. Since smart house has the characteristics of low power consumption, low cost and easy operability, ZigBee technology is adopted as a wireless network standard and CC2530 is selected as a sensor node. In the designed system, electric appliances can be controlled by voice.

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.

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