Design and Construction of a Chess Robot

In this paper, the design of a system that controls home appliances using voice commands is considered. This system may be utilized by people with special needs and the elderly. By using just their voice, they can control the lighting of their room, and turn on or off their television, air conditioner, or fan with safety and security and without needing someone else's assistance. This may be achieved by passing their voice commands to a microcontroller, (Arduino), through a device that uses voice or speech recognition technology. Herein, the system is designed at the lowest possible costs. Two basic ways are discussed to build this system, a wired system that does not depend on wireless technologies and the other depends on Bluetooth technology. Each of them has advantages and disadvantages. The hardware parts utilized in the design process are the Arduino Uno, Relay Module, and voice recognition module. The latter could be replaced by a Bluetooth module and a smartphone with an application that uses voice or speech recognition technology. The proposed wired system proved to be advantageous in terms of privacy, security and reliability. A comparison between the two systems is concluded at the end of this paper.

The project's goal is to develop a voice recognition and Bluetooth communication-based system for managing an induction motor's speed. The system is made up of two primary components: the speech recognition module, which is in charge of understanding user voice instructions, and the motor control module, which regulates to response to user voice commands. A speech recognition algorithm processes the user's vocal commands after being captured by the voice recognition module's microphone. control module receives the commands from the algorithm via Bluetooth communication. PWM method is used by the module to adjust the speed of induction after receiving commands. Without the use of physical buttons or switches, voice recognition technology offers customers a simple and practical way to adjust the motor's speed. The study shows that voice recognition technology and Bluetooth connectivity may be used to regulate the speed of induction motors, providing a practical and user-friendly solution for a variety of applications. Key Word: Induction motor, voice recognition, pulse-width modulation.

Nowadays, most hospitals have new problem that is lack of medical nurse due to the number of patient increas rapidly. The patient especially with physical disabilities are difficult to control the switch on electrical appliances in patient’s room. This research aims to develope voice recognition based home automation and being applied to patient room. A miniature of patient’s room are made to simulate this system. The patient's voice is received by the microphone and placed close to the patient to reduce the noise.V3 Voice recognition module is used to voice recognition process. Electrical bed of patient is represented by mini bed with utilising motor servo. The lighting of patient room is represented by small lamp with relay. And the help button to call the medical nurse is represented by buzzer. Arduino Uno is used to handle the controlling process. Six basic words with one syllable are used to command for this system. This system can be used after the patient's voice is recorded. This system can recognize voice commands with an accuracy 75%. The accuracy can be improved up to 85% by changing the voice command into two syllables with variations of vowels and identical intonation. Higher accuracy up to 95% can be reached by record all the subject’s voice.

In today's modern era, electronic devices have become a necessity that is often used in everyday life. With the development of increasingly advanced science and technology, many things can be used to meet the needs in terms of controlling electronic devices, one of which is controlling electronic devices using voice commands, where this system can be used for people with hand disabilities. In this research, a system will be made using Voice Recognition Module V3 as voice recognition to turn on and turn off electronic devices. The Voice Recognition Module will receive input in the form of voice commands via the microphone as a transducer and is connected to Arduino uno as the main microcontroller which will access the Control Panel which consists of Relay and Contactor components as controlled objects connected to Electronic Devices (Lamps, TV and AC). In the results of the system research, the percentage of successful speech recognition according to the voice sample is 96.6% from 10 times the pronunciation of the command given to each command. While the percentage of success when giving orders only with fragments of words is 21.25%. At the success rate of giving voice commands to different people, the percentage of success is 81%. The success rate for giving commands will be more responsive when in a room without noise or conducive, but the success rate for giving commands will decrease when pronunciation is at a distance of 1M.

Background and Objective: Traditional manual wheelchairs provide mobility to individuals with physical impairments but are poorly suited for individuals with a combination of physical and cognitive or perceptual impairments. Manual wheelchairs are more physically demanding than powered wheelchairs; however, powered wheelchairs require cognitive and physical skills that not all individuals possess. The general objective of this study is to develop a voice-controlled wheelchair that allows a disabled person to move around independently using a voice-recognition application that is interfaced with motors. The study will be beneficial for quadriplegic individuals who are paralyzed in both arms and both legs.Material and Methods: This study aims to modify a standard wheelchair controlled by voice commands where the EasyVR 3 Voice Recognition Module, ultrasonic sensors, microcontroller, and 12V wiper motor were integrated. Based on the signal given by the motor driving circuit, the controller switches the motor accordingly. The added safety feature is the ultrasonic sensor that senses obstacles with a fall detection system and sends a signal to the microcontroller to stop the chair.Results: Through testing and evaluation, the device’s functionality was proven to meet the desired objectives, and the limitations of the device were concluded. The motors and sensors were also found to be 100% functional. The average speed of the wheelchair is 0.2 m/s, and it can move with the user weighing up to 80 kg. The wheelchair lifts at an angle of up to 10˚. The overall acceptability of the unit, analyzed using statistical parameters like mean method and standard deviation analysis, gives a 4.53 average, 4.53 on usability, 4.07 on correctness, 4.37 on control, 4.50 on reliability, 4.33 on safety, and 4.8 on comfort, which means the unit meets the objectives.Conclusion: Based on the evaluation results, the project met the given objectives. The system was able to move following the voice command given. The device also proved its functionality, responsiveness, usability, correctness, control, reliability, safety, and comfortability. While the current study demonstrates the feasibility of voice-controlled wheelchairs, future research should focus on improving the accuracy and robustness of voice recognition systems and the incorporation of sensory feedback mechanisms, such as haptic feedback or auditory cues.

Most door accesses used in homes still use conventional keys. Where the use of manual keys is still vulnerable to loss or damage and is not very safe to use, because manual keys can be duplicated or duplicated by other people. This certainly feels less practical and flexible. This research aims to help improve door security. With a voice recognition system, only certain people can access it using a certain access code. Researchers used the trial and error method. The factor being tried is the voice recognition V3 module which can read voice recordings. The results of this research can be implemented in the form of a tool, where the system can open and close house doors according to the planned design, namely through voice commands and the designed system can run normally according to the automatic system that has been designed in prototype form. The conclusion from this research is that the voice recognition module is capable of recording sounds up to a distance of 20 cm. In voice recording < 10 cm the module is relatively easier to receive voice commands, in recording > 10 cm and < 15 cm the module is slightly less able to receive voice commands, so that in voice recording at a distance of 15 cm to 20 cm the module is very poor in receiving commands sound well.

Intelligent wheelchairs are becoming more and more prevalent in contemporary life, and the peaceful interaction of humans with wheelchairs is one of the most popular research topics. The development of a voice recognition and emotion recognition based intelligent wheelchair framework is being addressed here for truly impaired/disabled people who are unable to operate the wheelchair by hand. The patient can operate the wheelchair using voice commands, and the wheelchair’s Emotion Analysis module recognizes the patient’s face and records the patient’s emotions before sending the information to a cell phone application. A portion of the intelligent wheelchair is made to gather crucial information given by other units and send out emergency calls or notifications to the caregivers. Face recognition technology uses image processing to identify facial expressions by detecting the patient’s face and facial expressions. This helps the other components collect and send data via Internet of Things technologies. Speech – to –Text and Text – to-Speech Methodology is used in the voice recognition module and it captures the voice command data set and extracts the features of the commands.The model is already built and trained to recognize the commands and to send action request to the relevant unit.The Responsive AI auto starts the timer when the patient moves away from the wheelchair, recognizes time and responses back. This unit auto also sends the alert and calls to the guardian when the user has no response.

In the present scenario, when the automation has gain so much strength, all the support and machinery to human conversation are getting linked with voice controls. In all the field be it Internet of things, artificial intelligence or communication. In order to reduce the efforts on giving instructions and implementing them, the world has changed its behavior toward voice recognition. The voice speech recognition allows the user to understand the spoken voice commands and generate the result on the basis of that. This deals with the voice received and generating outputs based on the hearing capability of the machine. The result is generated and is made available for the further. Voice-based devices or applications are growing a lot. It uses state art process in speech-to-text, natural language understanding, deep learning and text-to-speech. The first step to build a voice application is to listen for user voice constantly and then understand the voice to understand and implement things. This deals with understanding in various languages under the section and reflects the work assigned to it. Speech recognition which is also known as automatic speech recognition (ASR) and voice recognition recognizes the spoken words and phrases and converts them to a machine-readable text, and speech recognition technology let users control digital devices by speaking instead of using conventional tools such as keystrokes, buttons or keyboards. From automated phone systems to Google voice to digital assistant, i.e., voice recognition, ASR helps in daily life activities. Even the bluetooth used in cars uses ASR. Voice recognition has taken a complete scan all over the arena. The tool of automation in voice further deals with the communication among the machines without the code access and suggestively talking with the help of compatible recognizable words. This would strengthen the compatibility and speed up the automation process by decreasing the amount of efforts made. Such work would overcome the error and would possibly give a better way of transformation. As Edmund L. Andrews researcher from Stanford recently on March 23, 2020 said that the possibility of error could be minimized to a great extent with the evolution under this process.

This paper describes intelligent voice controlled wheelchair which operates on user’s voice commands. The disabled people cannot move from one place to another on their own. They continuously need someone to help them in getting the wheelchair moving. This voice controlled system makes them more independent. A voice controlled wheelchair can provide easy access for physical disabled person who cannot control their movements especially by hands. This voice controlled wheelchair helps them to drive the wheelchair without anyone’s help. This system can be controlled by the simple voice commands given by the user. Depending upon the direction specified in the commands, the Arduino will drive the motors. The speech recognition is done by voice recognition module, connected with Arduino. The principle of the developed wheelchair consists of motor system, voice recognition module that would be controlled by the microcontroller. The automatic obstacle detection system is included to the developed wheelchair by using ultrasonic sensors in order to break the developed wheelchair immediately when any obstacles suddenly come in the way of the developed wheelchair. Therefore, the developed voice controlled wheelchair can provide easy access for people with physical disability and also offer automatic protection from obstacle collision if the mistake of any voice commands occurs.

The vast development of the technology of embedded systems has had a great impact on the healthcare field. Using low-cost, robust parts, this research proposes an innovative technology and design that enables paralyzed patients or elderly individuals to have a smart room with a voice recognition control unit that works like a joystick for various purposes. The aim is to create an environment that meets their needs and increases their independence, thereby improving their quality of life. The research will show the design of the control unit and present the various applications that can be programmed using voice commands, such as a wheelchair, bed, temperature, lights, TV, and alarm. The voice recognition module will be trained using the patient's voice, for example, to change the movement direction of a wheelchair. The system is based on training the Voice Recognition Module v3 with the use of Arduino and Node MCU. The results of the commendable accuracy of the English word response in a quiet environment ranged between 90% and 100% at the 0.2-meter distance and 50% and 100% at the 0.5-meter distance. While in a noisy environment, it ranged between 40% and 100% at the 0.2-meter distance and 10%–90% at the 0.5-meter distance. As for the Arabic-pronounced words, they ranged between 60% and 100% at the 0.2-meter distance and 30% and 100% at the 0.5-meter distance in a quiet environment. And, in a noisy environment, it ranged between 30% and 100% at the 0.2-meter distance and 10% and 100% at the 0.5-meter distance.

The aim of this study was to evaluate the potential of using voice recognition software in patient assessment documentation in mountain rescue. An exploratory experimental study was conducted, which involved 5 mountain rescue (MR) team members, 3 people who volunteered to act as patients, and the authors of the report who acted as observers. The MR personnel were asked to assess the patients and to document their findings using both voice recognition (VR) software and pen and paper. Data was collected using a questionnaire, observations were made by the authors and a comparison of written and VR digital documentation was conducted. The major concerns raised by the MR personnel were anticipated problems with the equipment such as lack of battery power, failure of the software to work effectively, and environmental factors. It was found that VR worked best when short simple sentences were used. Further robust research should be carried out in this area to critically evaluate potential use of VR in patient assessment documentation in MR.

Smart assistants are a technology that has become very popular today, due to the multiple functions they have, and somehow allow a natural interaction between devices and human beings. The objective is to develop an assistant based on NLP (Natural Language Processing) focused on the Java programming language, with the feature of guiding the user on the use of this language from reliable and validated sources, through speech recognition and speech synthesis by the assistant, allowing communication between the software and the user through natural language, in order to make the time in the consultation of information more efficient since it is considered that from the implementation of the speech to text engine and the subsequent processing of natural language, The search will be carried out on the web obtaining relevant results of precision. In the implemented methodology, the general requirements were defined, such as the voice recognition and identification modules, the search module and the internal storage structure, the design was based on a file-based controller view architecture, implemented through technologies such as PyQt5, Speech Recognition, Pyttsx3, Beautiful Soap among others, developed with the python programming language with the paradigm of object-oriented programming obtaining satisfactory results of precision in the searches by concepts and syntax carried out

Education and improved software, can it improve voice recognition errors in radiology reports?

This study explored whether over-the-counter continuous voice recognition software could be used to support the delivery of a standardized reading curriculum to adults with low-level literacy skills. Three primary questions were addressed in the study. First, how readily could mass-market continuous voice recognition software programs be adapted for use in adult literacy training? Second, what role(s) might the voice recognition technology play in facilitating the computer-based delivery of a standard text-based reading curriculum? And third, does the use of the voice recognition software positively affect the technological skills and computing comfort levels of adults with low-level literacy skills? Five adults with low-level literacy skills completed the computer-based curriculum, using the voice recognition software to practice and check their reading and writing efforts. A literacy tutor guided the participants through the curriculum, recorded and saved the participants' responses and videotaped the sessions for subsequent analysis. The findings reported here suggest that currently available over-the-counter continuous voice recognition technology, while essentially effective and accurate with fluent readers, is not yet ready, as a stand-alone system, to meet the needs of these adults with low-level literacy skills. The voice recognition software was most effective when it was used in the presence of a tutor. Having tutors provide on-going and immediate support to learners was a vital component of literacy training in this computer-based environment. In general the computer-based programs seemed to provide participants with a `motivational boost'. Specifically, the computer-based lessons helped develop participants' technological skills and confidence levels and promoted sustained focus on instructional tasks. Implications associated with these findings for future research with voice recognition software and adult literacy training are discussed.

As an implementation of the application of nuclear power for large-scale power plants, BATAN will build a Non-Commercial Power Reactor (RDNK) or Experimental Power Reactor (RDE). RDNK operation needs to consider the several aspects, including the aspect of nuclear security. The scope of aspects of nuclear security can be in the form of controlling personnel who access RDNK, especially in limited areas. Reliability of hardware systems and supporting software needs to be created to ensure nuclear security. The purpose of this study is to design a personnel access verification system using voice and gesture recognition through a camera to support the development of the detection and response system of the RDNK test facility. This is related to the development of nuclear security and safeguard RDNK. Personnel verification system development using voice recognition that has been built previously and carried out additional features in the form of gesture recognition. The addition of the recognition feature will strengthen the guarantee of personnel who have access through voice recognition. Besides the benefits of adding gesture recognition features are also expected to be able to identify suspicious personnel behavior. The gesture recogntion feature will be unified on the same hardware as voice recognition. This hardware will be programmed using the Digital Signal Processing (DSP) prototype module. The DSP module will be designed by the research team using a 32-bit controller embedded with voice recognition and gesture recognition software using the Artificial Neural Network (ANN) method. Software on DSP uses the C programming language. Storage of sound database and gestures of personnel entering and leaving the RDNK installation will be carried out by an embedded computer. Personnel database monitoring can be monitored through Computer Personnel (PCs) in real time using LAN-based monitoring. This circuit type is expected to realize the guarantee of nuclear security in the scope of personnel access.