scholarly journals Prototipe Pengaman Pintu Rumah Menggunakan Voice Recognition dengan EasyVR Berbasis Mikrokontroler

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Syaeful Ulum ◽  
Maun Budiyanto
Keyword(s):  
Speech Recognition ◽  
Voice Recognition ◽  
Safety Factors ◽  
Achievement Level ◽  
Recognition Process ◽  
The Voice

The adventages of technology make every job easier, but this ease sometimes isn’t matched by safety factors. Security is vital to avoiding this technology being misused by uninvited people.This journal discusses the security of home doors with a microcontroller-based voice. The voice recognition process starts from the sound that propagates and then processes the corresponding easyvr sensor so that the easyvr sends a command to the relay to open the doorlock solenoid. From various tests obtained from voice recognition that can support the sound in the form of recordings, in speech recognition with an achievement level of 45 dB approved sound with an ideal pitch at 0-700 cm, it needs 75 dB sound amplifier with an ideal distance of 0-20 cm. For the percentage of success range with 30-40% different and the percentage of sound success is above 90%.Kemajuan teknologi membuat pekerjaan menjadi mudah, namun kemudahan tersebut tidak diimbangi dengan faktor keamanan. Keamanan menjadi hal yang vital untuk menghindari teknologi tersebut tidak disalahgunakan oleh orang yang tidak berwenang. Pada jurnal ini membahas pengaman pintu rumah dengan pengenalan suara berbasis mikrokontroler. Proses pengenalan suara dimulai dari suara yang merambat lalu diproses sensor easyvr jika sesuai sampling maka easyvr mengirimkan perintah kepada relay untuk membuka solenoid doorlock. Dari berbagai pengujian didapatkan bahwa pengenalan suara tidak dapat mengenali suara dalam bentuk rekaman, pada pengenalan suara dengan tingkat kebisingan 45 dB mengenali suara dengan ideal  pada jark 0-700 cm, kebisingan 75 dB mengenali suara dengan ideal pada jarak 0-20 cm. Tingkat persentase keberhasilan suara yang berbeda 30-40% dan persentase keberhasilan suara yang sama diatas 90%.

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>

scholarly journals Design and Development of Hand Disabilities Tool To Turn On and Off Electronic Devices Using Voice Recognition Module V3

2016 ◽  
Vol 3 (2) ◽  
pp. 47-52
Author(s):  
Anas Ardi Firmansyah
Keyword(s):  
Speech Recognition ◽  
Everyday Life ◽  
Success Rate ◽  
Electronic Devices ◽  
Voice Recognition ◽  
Control Panel ◽  
System Research ◽  
Turn On ◽  
The Voice ◽  
Modern Era

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. 

scholarly journals Review on Automated Elevator-an Attentive Elevator to Elevate using Speech Recognition

2021 ◽  
Vol 08 (1&2) ◽  
pp. 20-26
Author(s):  
Vishakha Patil ◽  
Keyword(s):  
Speech Recognition ◽  
Present Status ◽  
Voice Recognition ◽  
Recognition System ◽  
Modern World ◽  
Motor Module ◽  
The City ◽  
The Voice ◽  
Transport Device ◽  
Over Time

Elevator has over time become an important part of our day-to-day life. It is used as an everyday transport device useful to move goods as well as persons. In the modern world, the city and crowded areas require multiform buildings. According to wheelchair access laws, elevators/lifts are a must requirement in new multi-stored buildings. The main purpose of this project is to operate the elevator by voice command. The project is operating based on voice, which could help handicap people or dwarf people to travel from one place to another without the help of any other person. The use of a microcontroller is to control different devices and integrate each module, namely- voice module, motor module, and LCD. LCD is used to display the present status of the lift. The reading edge of our project is the “voice recognition system” which genet’s exceptional result while recognizing speech.

Design and Implementation of Speech Recognition System Based on FPGA

2013 ◽  
Vol 416-417 ◽  
pp. 1156-1159
Author(s):  
Bo Nian Yi
Keyword(s):  
Speech Recognition ◽  
Information Technologies ◽  
Voice Recognition ◽  
Recognition System ◽  
Recognition Algorithm ◽  
Characteristic Parameters ◽  
The Core ◽  
New Information ◽  
And Control ◽  
The Voice

Speech recognition technology is one of the hottest and the most promising new information technologies in the world. This paper studied the voice pretreatment and extractions of MFCC characteristic parameters, constructed speech keywords recognition algorithm with the core of the VQ model and the HMM model, using MATLAB to complete the training and simulation of algorithm, FPGA-based voice recognition technology, and the simulation and implementation of its hardware and software. It laid the foundation for the realization of speech recognition and control based FPGA.

Automated Speech Recognition as a Function of Formal Speech Training and Passage of Time between Template Training and Testing

1985 ◽  
Vol 29 (10) ◽  
pp. 937-941
Author(s):  
Daryle Jean Gardner ◽  
David DeFruiter ◽  
Mark Keith ◽  
Mike Kline ◽  
Michael Dresel ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Recognition Performance ◽  
Voice Recognition ◽  
Recognition System ◽  
Voice Training ◽  
Automated Speech Recognition ◽  
Speech Training ◽  
The Voice ◽  
Vocabulary Recognition

The purpose of the present study was to assess the longevity of templates trained using a speaker-dependent voice recognition system, and to determine whether recognition varies with the degree of formal speech training. Results indicate that vocabulary recognition is fairly stable over a two-month period, and that subjects with formal voice training do not appreciably differ in performance from novice speakers. However, experience with the voice recognition system did result in improved recognition performance for both trained and novice speakers.

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.

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.

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