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.

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 A Fundamental of Automatic Speech Recognition and Speech Database

2021 ◽  
Vol 9 (9) ◽  
pp. 1020-1027
Author(s):  
Sonal Anilkumar Tiwari
Keyword(s):  
Speech Recognition ◽  
Mobile Phones ◽  
Automatic Speech Recognition ◽  
Recognition System ◽  
Speech Recognition System ◽  
Speech Database ◽  
The Voice

Abstract: This can be quite interesting when we think that we commanding something to in-animated objects. Yes it is possible with the help of ASR systems. Speech recognition system is a system that can make humans to talk with machineries. Nowadays speech recognition is such a technique that without it, a person cannot do any of his work properly. People get addicted of it. And it has become a habit for humans like we use mobile phones but when we want to type something, then we immediately can pass the voice commands. With which our Efforts are reduced, as well as a lot of our time. Keywords: Speech, Speech Recognition, ASR, Corpus, PRAAT

A Comparison of Three Methods for Controlling Aircraft Systems

1986 ◽  
Vol 30 (7) ◽  
pp. 638-641
Author(s):  
John P. Zenyuh ◽  
John M. Reising
Keyword(s):  
Control Systems ◽  
Relative Effectiveness ◽  
Voice Recognition ◽  
Recognition System ◽  
Control Device ◽  
Control Mode ◽  
Aircraft Systems ◽  
Remote Touch ◽  
The Voice ◽  
Speed And Accuracy

The objective of this study was to compare the relative effectiveness of three modes of subsystem control: a voice recognition system with visual feedback presented on the head-up display, a standard multifunction control device with tailored switching logic, and a remotely operated multifunction control with feedback presented on the head-up display. Comparisons were based on measures of interference with a loading task and overall speed and accuracy of the control operations performed. The working hypothesis was that the voice system and head-up multifunction control would manifest substantially lower interference with the primary task, while subsystem control operation times would remain unaffected by control mode. The results indicate that performance with the remote touch panel was significantly poorer than with the voice or standard multifunction control systems.

scholarly journals Automatic Speech Recognition in Mobile Customer Care Service

2015 ◽  
Vol 4 (01) ◽  
pp. 07-11
Author(s):  
Ms. Pooja Sahu
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Care Service ◽  
Recognition System ◽  
Care Services ◽  
Mobile Shopping ◽  
Customer Care ◽  
The One ◽  
The Individual ◽  
The Voice

In the project an automatic speech system is used in mobile customer care   services. In existing  mobile  customer care  services, customer  have  to  wait for 4 to 5 minutes  to get  into the  option  what   they  want to  inquire. Based on the requirement, we go for filtering the incoming calls. Persons who require particular data are dynamically move to speech recognition system that identifies the type of the enquiry chosen. Speech recognition is the one which dynamically identifies the individual speaking based on analyzing the speech waves. It helps in identifying the voice of the speaker to know the recognized user. It also helps in accessing services like telephone banking, mobile shopping, database services and securing the information which is confidential.

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 Implementation of Voice Recognition Via CNN and LSTM

2020 ◽  
Vol 9 (4) ◽  
pp. 1842-1844
Keyword(s):  
Feature Extraction ◽  
Low Cost ◽  
Voice Recognition ◽  
Recognition System ◽  
Computational Costs ◽  
The Voice

The voice recognition system uses CNN a lot. This is because CNN has the optimized ability to recognize and classify targets. CNN, however, has a problem that the bigger the object to be recognized, the more expensive the computational costs are. In this paper, we are going to solve these problems through MFCC feature extraction and model roll combining CNN and LSTM to present the possibility of performing voice recognition even through low-cost devices.

scholarly journals Remote Control using Voice Recognition based on Arduino

2019 ◽  
Vol 12 (3) ◽  
pp. 22-28
Author(s):  
Jinan N. Shehab
Keyword(s):  
Remote Control ◽  
Low Cost ◽  
Voice Recognition ◽  
Recognition System ◽  
Home Automation ◽  
Easy Method ◽  
C Language ◽  
Infrared Technology ◽  
Data Coordination ◽  
The Voice

Home automation becomes important, because it gives the user convenient and easy method to use home appliances. This paper aims to help people with special needs or physical disabilities and injuries by paralysis to control any device using infrared technology using voice commands based on the voice recognition system (voice recognition unit V3) system can recognize voice commands, convert them to desired data coordination and data transmission via IR transmitter and microcontroller (Arduino Uno) Receiving this signal by IR sensor to control TV receiver then get a full remote control that works by voice commands. The software consists of a Micro C language programmable microcontroller. This system is of low cost and flexible with growing variety of devices that can be controlled.

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