scholarly journals Automatic Vehicle Turn Indicator using Speech Recognition

2019 ◽  
Vol 8 (3) ◽  
pp. 6697-6700
Keyword(s):  
Regular Language ◽  
Voice Recognition ◽  
Human Communication ◽  
Signaling Systems ◽  
Turn Indicator ◽  
Voice Control ◽  
Language Control ◽  
Equipment Manufacture ◽  
Manual Tasks ◽  
The Voice

Voice-controlled innovation is an energizing region of research that is utilized to help people in the mechanical control of manual frameworks. It is a part of human-communication that builds the advances in programmed discourse acknowledgment or ASR with the inventive advances of characteristic language handling or NLP. Wise frameworks, for example, Automatic Vehicle Signaling Systems, can likewise take into consideration adaptability in manual activities. In late investigations, analysts have investigated regular language control of manual tasks. In this paper we will research interfacing voice control activities with Arduino-based equipment stages that are utilized to structure the programmed sign highlights in a vehicle. The control system includes a voice recognition circuit for activating turn signal devices within the vehicle. The voice recognition circuit takes in input from the voice from the Google maps voice assistant. In some formats, a wireless hardware is provided while in other embodiments original equipment manufacture is accommodated

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.

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.

RISK CALCULATION AND THREAT ASSESSMENT OF THE USE OF VOICE CONTROL SYSTEMS IN TRUSTED DISTRIBUTED COMPUTER SYSTEMS

2021 ◽  
pp. 93-104
Author(s):  
Александр Александрович Хайдаров ◽  
Александр Сергеевич Шишлов ◽  
Николай Николаевич Толстых
Keyword(s):  
Control Systems ◽  
Voice Recognition ◽  
Threat Assessment ◽  
Distributed Computer System ◽  
Dynamic Transformation ◽  
Algorithmic Support ◽  
Voice Control ◽  
Recognition Systems ◽  
The Stability ◽  
The Voice

Цель исследования состоит в повышении защищенности элементов распределенной компьютерной системы автоматического распознавания голосовых команд от возможного неверного определения команды за счет создания алгоритмического обеспечения оценки и регулирования рисков неверной идентификации голосовой команды для сравнения реализации двух алгоритмов: алгоритм динамической трансформации временной шкалы и алгоритм на основе скрытых Марковских процессов.Полученные результаты могут быть использованы или адаптированы при необходимости повышения стойкости систем автоматического распознавания голосовых команд на этапах проектирования и модернизации, а также при необходимости восстановления эффективности функционирования после компрометации или взлома. The aim of the study is to increase the security of the elements of a distributed computer system for automatic recognition of voice commands from possible incorrect identification of the command by creating algorithmic support for assessing and managing the risks of incorrect identification of the voice command to compare the implementation of two algorithms: the algorithm for dynamic transformation of the timeline and the algorithm based on hidden Markov processes.The obtained results can be used or adapted if it is necessary to increase the stability of automatic voice recognition systems at the design and modernization stages, as well as if it is necessary to restore the efficiency of functioning after a compromise or hacking.

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.

Lampu Sein Helm Sepeda Berbasis Voice Recognition

2019 ◽  
Vol 11 (01) ◽  
pp. 20-25
Author(s):  
Indra Saputra ◽  
Parulian Silalahi ◽  
Bayu Cahyawan ◽  
Imam Akbar
Keyword(s):  
Voice Recognition ◽  
Driving Safety ◽  
Bicycle Helmet ◽  
Turn Signal ◽  
Voice Command ◽  
The Voice ◽  
Indicator Signal

Bicycles are not equipped with the turn signal. For driving safety, a bicycle helmet with a turn signal is designed with voice rrecognition. It is using the Arduino Nano as a controller to control the ON and OFF of turn signal lights with voice commands. This device uses a Voice Recognition sensor and microphone that placed on a bicycle helmet. When the voice command is mentioned in the microphone, the Voice Recognition sensor will detect the command specified, the sensor will automatically read and send a signal to Arduino, then the turn signal will light up as instructed, the Arduino on the helmet will send an indicator signal via the Bluetooth Module. The device is able to detect sound with a percentage of 80%. The tool can work with a distance of <2 meters with noise <71 db.

ANALYSIS OF VOICE CUES IN RECOGNITION OF SARCASM

2019 ◽  
Vol 12 ◽  
Author(s):  
Basavaraj N Hiremath ◽  
Malini M Patilb
Keyword(s):  
Feature Extraction ◽  
Computer Program ◽  
Principle Component Analysis ◽  
Voice Recognition ◽  
Component Analysis ◽  
Recognition System ◽  
Principle Component ◽  
Whole Process ◽  
The Voice

The voice recognition system is about cognizing the signals, by feature extraction and identification of related parameters. The whole process is referred to as voice analytics. The paper aims at analysing and synthesizing the phonetics of voice using a computer program called “PRAAT”. The work carried out in the paper also supports the analysis of voice segmentation labelling, analyse the unique features of voice cues, understanding physics of voice, further the process is carried out to recognize sarcasm. Different unique features identified in the work are, intensity, pitch, formants related to read, speak, interactive and declarative sentences by using principle component analysis.

Voice Assistant — Application of Speech Recognition Technology in the Android System

2014 ◽  
Vol 596 ◽  
pp. 384-387
Author(s):  
Ge Liu ◽  
Hai Bing Zhang
Keyword(s):  
Speech Recognition ◽  
Service Providers ◽  
Voice Recognition ◽  
Working Process ◽  
Bottleneck Problems ◽  
Speech Recognition Technology ◽  
Android System ◽  
The Voice

This paper introduces the concept of Voice Assistant, the voice recognition service providers, several typical Voice Assistant product, and then the basic working process of the Voice Assistant is described in detail and proposed the technical bottleneck problems in the development of Voice Assistant software.

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>

INFORMATION SYSTEM FOR PEOPLE WITH HEARING IMPAIRMENT

2021 ◽  
Vol 335 (1) ◽  
pp. 54-59
Author(s):  
Y.S. Nurakhov ◽  
A.E. Kami
Keyword(s):  
Quality Of Life ◽  
Information System ◽  
Public Life ◽  
Voice Recognition ◽  
Hearing Impairments ◽  
Hardware Complex ◽  
Software And Hardware ◽  
Functional Blocks ◽  
The Voice

The article presents the development of an information system for recognizing voice into text for people with hearing impairments, which makes it possible to improve the quality of life and interaction in society with other people. The device, software, functional blocks and subsystems of the information system are described. Examples of possible application and placement of the system in various spheres of public life are given. One of the types of implementation of the voice recognition information system is described. The development and creation of prototypes of a device for people with hearing impairments is considered. In the course of the research, the Google Speech Api technology was selected for speech recognition. In addition, this article presents a software and hardware complex that allows you to translate speech into text and then display it on the screen. Arduino UNO-based devices were chosen to achieve the goal. All information is processed on the smartphone of people with hearing impairments, which is sent to the device via Bluetooth with Arduino.

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