scholarly journals Smart Bed Using Voice Recognition for Paralyzed Patient

2020 ◽  
Vol 854 ◽  
pp. 012045
Author(s):  
Nurul Fadillah ◽  
Ahmad Ihsan
Keyword(s):  
Voice Recognition ◽  
Paralyzed Patient

The effect of speech idiosyncrasies on voice recognition: Is it a laughing matter?

1997 ◽  
Author(s):  
Craig B. Neely ◽  
Jeffrey R. Wilson ◽  
Brian H. Bornstein
Keyword(s):  
Voice Recognition

Toward speaker independent voice recognition

1982 ◽  
Author(s):  
Gary K. Poock ◽  
Norman D. Schwalm ◽  
Ellen F. Roland
Keyword(s):  
Voice Recognition ◽  
Speaker Independent

Initial validation of voice recognition interpretation methodology

2011 ◽  
Author(s):  
Jeffrey A. Daniels ◽  
Maria J. Amores ◽  
Jennifer Haist ◽  
Susan Chamberlain ◽  
Karianne Bilsky ◽  
...  
Keyword(s):  
Voice Recognition ◽  
Initial Validation

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.

Items Searching in Factory Warehouse Using Arduino Module

2019 ◽  
Vol 1 (1) ◽  
pp. 1-14
Author(s):  
Tan Liong Ching ◽  
Nureize Binti Arbaiy
Keyword(s):  
Inventory Management ◽  
Liquid Crystal Display ◽  
Light Emitting Diode ◽  
Storage System ◽  
Voice Recognition ◽  
Inventory System ◽  
Search Process ◽  
Light Emitting ◽  
Recognition Function ◽  
Light Function

The smart store system (F3 Storage System) provides an inventory system function, and is supported by voice recognition for items searching purpose in the warehouse. This system is aimed to improve effectiveness in item searching process for the warehouse management. An inventory system structures is employed in this system to enable items management. Voice recognition facility helps the worker to search item in an effective way. Worker can use voice recognition function to search the item in the warehouse, and searched information of the item will be displayed in the liquid crystal display (LCD) screen. Meanwhile, the location of the item will be physically indicated by the light emitting diode (LED) light function. The developed system also contains a barcode system to enhance the process of scheduling warehouse activity. Such facilities will enhance the capabilities of existing inventory management systems in warehouses. Prototyping model is used to assist project development. Arduino technology is used to enable integrated hardware and software to read data or input. With Arduino technology, traditional search items by using text and search functionality are enhanced to allow speech functionality. This functionality makes the search process faster and more efficient.

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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