Keep talking—Performance effectiveness with continuous voice recognition for spreadsheet users

1997 ◽  
Vol 2 (1) ◽  
pp. 41-48
Author(s):  
Michael J. DeHaemer ◽  
George Wright ◽  
Margaret H. Richards ◽  
Thomas W. Dillon
Keyword(s):  
Voice Recognition ◽  
Performance Effectiveness ◽  
Continuous Voice Recognition

Keep talking—Performance effectiveness with continuous voice recognition for spreadsheet users

1995 ◽  
Vol 1 (1) ◽  
pp. 41-48 ◽  
Author(s):  
Michael J. DeHaemer ◽  
George Wright ◽  
Margaret H. Richards ◽  
Thomas W. Dillon
Keyword(s):  
Voice Recognition ◽  
Performance Effectiveness ◽  
Continuous Voice Recognition

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.

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