scholarly journals Implementation of Voice based Touchless Lift System

2021 ◽  
pp. 241-246
Author(s):  
B. Swathi ◽  
Akshay S Prathap ◽  
Aiswarya V Kumar ◽  
Ranjitha R ◽  
Raviteja Kaki
Keyword(s):  
Speech Recognition ◽  
Voice Recognition ◽  
Smart Phones ◽  
Physical Contact ◽  
Future Generations ◽  
Electronic Control ◽  
The Disabled ◽  
Transport Vehicle ◽  
Physically Challenged ◽  
Machine Communication

In this rapid world of technology where voice begins its era of domination to replace the touch screens from smart phones to huge computer systems, bringing voice in day to day affairs becomes significant. An elevator or lift is a transport vehicle that moves people or goods from on floor to another floor in a building. Typically push buttons were used to send requests to the elevators. In recent times touch buttons are coming to use. But now voice recognition can replace the push/touch technology. Elevators being one such system used in daily life serves this purpose of making future generations hands free which also becomes a boon for the disabled as well as helps during the pandemic situation to avoid physical contact. The main objective of this project is to propose and assemble a voice operated lift/elevator control system. The proposed system acts as human-machine communication system. This research combines electronic control technology with speech recognition technology. The input to the system is human speech. Speech recognition is the method of recognizing the vocal words to take the essential actions accordingly. This device is very helpful for paralysis, short height people and physically challenged persons.

Voice/Speech Recognition Software

2013 ◽  
pp. 1005-1011
Author(s):  
Andrew Kitchenham ◽  
Doug Bowes
Keyword(s):  
Speech Recognition ◽  
Assistive Technology ◽  
Special Needs ◽  
Learning Process ◽  
Voice Recognition ◽  
Special Needs Students ◽  
Speech Recognition Software ◽  
The Disabled ◽  
Recognition Software

In this chapter, the authors discuss the promise of speech or voice recognition software and provide practical suggestions for the teacher or any stakeholder working with a disabled child. The authors begin the chapter with a brief overview of the legislation mandating the accommodation of special needs students in the classroom and discuss the implications of assistive technology. The authors then move on to an examination of the promise of the software. The authors end the chapter with practical ideas for implementation should the caregiver believe that voice recognition software will assist the disabled child in the learning process.

scholarly journals Rancang Bangun Sistem Kendali Berbasis Googlespeech Untuk Aktivasi Peralatan Listrik Rumah

2018 ◽  
Vol 5 (2) ◽  
pp. 83-98
Author(s):  
Tesar Kurniawan ◽  
Nursin Nursin ◽  
Muhamad Amin Bakrie ◽  
Seta Samsiana
Keyword(s):  
Speech Recognition ◽  
Free Space ◽  
Recognition Accuracy ◽  
Voice Recognition ◽  
Smart Phones ◽  
Maximum Distance ◽  
Software Developer ◽  
Door Lock ◽  
App Inventor ◽  
Bahasa Indonesia

App inventor adalah media pengembang perangkat lunak untuk sistem android, yang memudahkan para  pengembangnya mengembangkan  idenya,  salah satunya aplikasi yang mampu mengendalikan peralatan listrik rumah menggunakan suara melalui  telepon  pintar  yang dapat mengontrol aktivasi peralatan listrik rumah. Google  Speech  digunakan untuk pengenalan suara yang  kemudian memberikan input ke Arduino untuk mengendalikan aktivasi peralatan listrik rumah, Peralatan listrik rumah seperti lampu, motor pompa akuarium, kipas, door lock dan motor servo yang memanfaatkan relay sebagai driver, kemudian dilakukanlah pengujian dan penelitian pada laporan ini berisi tentang pengujian akurasi pengenalan suara google  Speech dan pengujian jarak koneksi Bluetooth. Tingkat keakurasian pada google  Speech  yang paling baik dari 3 bahasa yaitu Bahasa Indonesia disusulBahasa jawa  dan terakhir Bahasa sunda, sedangkan untuk jarak koneksi pada Bluetooth dapat dioperasikan jarak maksimal pada ruang bebas adalah 20 m dan jarak maksimal pada ruang berhalangan adalah 13 m. App inventor is a software developer media for android systems, which makes it easy for developers to develop their ideas, i.e an application that is able to control home electrical appliances using voice over smart phones that can control the activation of home electrical appliances. Google Speech is used for voice recognition which then provides input to Arduino to control the activation of home electrical appliances, such as lamps, aquarium pump motors, fans, door locks. A servo motors is used as drivers, then test and research on this report Contains about Speech google speech recognition accuracy testing and Bluetooth connection distance testing. Level of accuracy on google Speech the best of 3 languages ie Indonesian followed by Java and last language Sundanese, while for the distance on the Bluetooth connection can be operated the maximum distance in free space is 20 m and the maximum distance in the absence room is 13 m.

Voice/Speech Recognition Software

2012 ◽  
pp. 98-104
Author(s):  
Andrew Kitchenham ◽  
Doug Bowes
Keyword(s):  
Speech Recognition ◽  
Assistive Technology ◽  
Special Needs ◽  
Learning Process ◽  
Voice Recognition ◽  
Special Needs Students ◽  
Speech Recognition Software ◽  
The Disabled ◽  
Recognition Software

In this chapter, the authors discuss the promise of speech or voice recognition software and provide practical suggestions for the teacher or any stakeholder working with a disabled child. The authors begin the chapter with a brief overview of the legislation mandating the accommodation of special needs students in the classroom and discuss the implications of assistive technology. The authors then move on to an examination of the promise of the software. The authors end the chapter with practical ideas for implementation should the caregiver believe that voice recognition software will assist the disabled child in the learning process.

scholarly journals Environmental effects on reliability and accuracy of MFCC based voice recognition for industrial human-robot-interaction

2021 ◽  
pp. 095440542110144
Author(s):  
B Birch ◽  
CA Griffiths ◽  
A Morgan
Keyword(s):  
Speech Recognition ◽  
Voice Recognition ◽  
Human Robot Interaction ◽  
Hole Drilling ◽  
Time Warping ◽  
Mel Frequency Cepstral Coefficients ◽  
Robot Interaction ◽  
Extraction Algorithm ◽  
Dynamic Time ◽  
Manufacturing Environments

Collaborative robots are becoming increasingly important for advanced manufacturing processes. The purpose of this paper is to determine the capability of a novel Human-Robot-interface to be used for machine hole drilling. Using a developed voice activation system, environmental factors on speech recognition accuracy are considered. The research investigates the accuracy of a Mel Frequency Cepstral Coefficients-based feature extraction algorithm which uses Dynamic Time Warping to compare an utterance to a limited, user-dependent dictionary. The developed Speech Recognition method allows for Human-Robot-Interaction using a novel integration method between the voice recognition and robot. The system can be utilised in many manufacturing environments where robot motions can be coupled to voice inputs rather than using time consuming physical interfaces. However, there are limitations to uptake in industries where the volume of background machine noise is high.

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.

A MULTILINGUAL APPROACH TO TASK-ORIENTED MAN-MACHINE DIALOGUE BY VOICE

1988 ◽  
Vol 02 (03) ◽  
pp. 573-588
Author(s):  
PHILIPPE MORIN ◽  
JEAN-PAUL HATON ◽  
JEAN-MARIE PIERREL ◽  
GUENTHER RUSKE ◽  
WALTER WEIGEL
Keyword(s):  
Speech Recognition ◽  
Electronic Mail ◽  
Dialogue Systems ◽  
Human Speech ◽  
Artificial Languages ◽  
Man Machine Dialogue ◽  
Machine Communication ◽  
Task Oriented ◽  
Multilingual Approach ◽  
Multimedia Interfaces

In the framework of man-machine communication, oral dialogue has a particular place since human speech presents several advantages when used either alone or in multimedia interfaces. The last decade has witnessed a proliferation of research into speech recognition and understanding, but few systems have been defined with a view to managing and understanding an actual man-machine dialogue. The PARTNER system that we describe in this paper proposes a solution in the case of task oriented dialogue with the use of artificial languages. A description of the essential characteristics of dialogue systems is followed by a presentation of the architecture and the principles of the PARTNER system. Finally, we present the most recent results obtained in the oral management of electronic mail in French and German.

scholarly journals Mobile Controlled Automated wheelchair for Disabilities

2019 ◽  
Vol 9 (1S) ◽  
pp. 240-244
Keyword(s):  
People With Disabilities ◽  
Disabled Persons ◽  
Smart Phones ◽  
Mobile Users ◽  
Android Application ◽  
Mobile Games ◽  
The Past ◽  
Wheel Chair ◽  
Physically Challenged ◽  
Tilt Change

As the usage of the Android smart phones has been considerably increasing, a lot of applications have been developed for the benefits of mobile users. In the past, many applications have been designed aiming to help physically disabled persons. This paper presents an android application which providers several options for controlling the movement of wheelchairs effectively. The proposed application enables People with Disabilities (PWDs) to operate the wheel chair with minimum effort. Apart from voice commands, the proposed application detects and measures the tilt change, and moves the wheelchair based on the degree of the tilt. It also provides a soft joystick as in mobile games to ease the operation of the wheelchairs. Furthermore, sensors that are fixed in the wheelchair can detect and avoid obstacles when the chair is on the move. Hence, it ensures the safety while using the wheelchairs. The proposed application will help both physically challenged persons and elders to operate the wheelchairs more comfortably.

Comparison of Voice-Automated Transcription and Human Transcription in Generating Pathology Reports

2003 ◽  
Vol 127 (6) ◽  
pp. 721-725
Author(s):  
Maamoun M. Al-Aynati ◽  
Katherine A. Chorneyko
Keyword(s):  
Speech Recognition ◽  
Voice Recognition ◽  
Computer Software ◽  
Continuous Speech ◽  
Continuous Speech Recognition ◽  
Accuracy Rate ◽  
Written Text ◽  
Computer Based ◽  
Pathology Reports ◽  
Recognition Software

Abstract Context.—Software that can convert spoken words into written text has been available since the early 1980s. Early continuous speech systems were developed in 1994, with the latest commercially available editions having a claimed accuracy of up to 98% of speech recognition at natural speech rates. Objectives.—To evaluate the efficacy of one commercially available voice-recognition software system with pathology vocabulary in generating pathology reports and to compare this with human transcription. To draw cost analysis conclusions regarding human versus computer-based transcription. Design.—Two hundred six routine pathology reports from the surgical pathology material handled at St Joseph's Healthcare, Hamilton, Ontario, were generated simultaneously using computer-based transcription and human transcription. The following hardware and software were used: a desktop 450-MHz Intel Pentium III processor with 192 MB of RAM, a speech-quality sound card (Sound Blaster), noise-canceling headset microphone, and IBM ViaVoice Pro version 8 with pathology vocabulary support (Voice Automated, Huntington Beach, Calif). The cost of the hardware and software used was approximately Can $2250. Results.—A total of 23 458 words were transcribed using both methods with a mean of 114 words per report. The mean accuracy rate was 93.6% (range, 87.4%–96%) using the computer software, compared to a mean accuracy of 99.6% (range, 99.4%–99.8%) for human transcription (P < .001). Time needed to edit documents by the primary evaluator (M.A.) using the computer was on average twice that needed for editing the documents produced by human transcriptionists (range, 1.4–3.5 times). The extra time needed to edit documents was 67 minutes per week (13 minutes per day). Conclusions.—Computer-based continuous speech-recognition systems in pathology can be successfully used in pathology practice even during the handling of gross pathology specimens. The relatively low accuracy rate of this voice-recognition software with resultant increased editing burden on pathologists may not encourage its application on a wide scale in pathology departments with sufficient human transcription services, despite significant potential financial savings. However, computer-based transcription represents an attractive and relatively inexpensive alternative to human transcription in departments where there is a shortage of transcription services, and will no doubt become more commonly used in pathology departments in the future.

scholarly journals Wheelchair Neuro Fuzzy Control and Tracking System Based on Voice Recognition

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2872 ◽  
Author(s):  
Mokhles M. Abdulghani ◽  
Kasim M. Al-Aubidy ◽  
Mohammed M. Ali ◽  
Qadri J. Hamarsheh
Keyword(s):  
Fuzzy Controller ◽  
Tracking System ◽  
Voice Recognition ◽  
Real Data ◽  
Communication Technologies ◽  
Real Time Control ◽  
Time Control ◽  
Smart Wheelchairs ◽  
Neuro Fuzzy ◽  
The Disabled

Autonomous wheelchairs are important tools to enhance the mobility of people with disabilities. Advances in computer and wireless communication technologies have contributed to the provision of smart wheelchairs to suit the needs of the disabled person. This research paper presents the design and implementation of a voice controlled electric wheelchair. This design is based on voice recognition algorithms to classify the required commands to drive the wheelchair. An adaptive neuro-fuzzy controller has been used to generate the required real-time control signals for actuating motors of the wheelchair. This controller depends on real data received from obstacle avoidance sensors and a voice recognition classifier. The wheelchair is considered as a node in a wireless sensor network in order to track the position of the wheelchair and for supervisory control. The simulated and running experiments demonstrate that, by combining the concepts of soft-computing and mechatronics, the implemented wheelchair has become more sophisticated and gives people more mobility.

scholarly journals Vision Controlled Robotic System

2019 ◽  
Vol 9 (1S) ◽  
pp. 188-191
Keyword(s):  
Motor Neuron ◽  
Touch Screen ◽  
Dc Motor ◽  
Disabled Persons ◽  
Robotic System ◽  
Future Generations ◽  
Eye Tracker ◽  
Highly Efficient ◽  
The World ◽  
The Disabled

The field of robotics is changing the world in which we live today and the future generations will be largely served by various robotic services which will be highly efficient and dynamic. Offering affordable and efficient robotic services to the society is the need of the hour and this project is highly inclined towards this theme. The latest touch screen technology and the use of mechanical components like joysticks can be replaced by Gesture Controlled Robotics. The product is aimed at improving the conditions of motor neuron disabled persons using OpenCV libraries of Processing3 software and Arduino Uno (Atmega328 microcontroller). The vision of the disabled person is sensed using a Glass Eye Tracker and every 25th frame of the picture (here it is the pupil) is sent to the Processing3 software. This software processes the image based on the algorithm. The ports of Processing3 software and Arduino are serially communicated. Now the Arduino performs the output part with the help of L293D motor driver and 24V DC motor.

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