Name
Abstract | ||
|---|---|---|
There are many different types of sign languages that are used around the world which are important as the medium of conversation among hearing impaired community. However, majority of hearing people do not know or understand sign languages. Thus, communication between a hearing-impaired person and a hearing person is a difficult issue. In order to solve this problem, this project proposes a development of a dual-sensor based sign language translator. The goal of the project is to translate sign language into speech and display on screen by using the device. The device was developed in a glove-based system which was able to read the movements of every finger and arm using two (2) types of sensors, an accelerometer and five (5) units of flex sensors. This paper describes the design of the glove-based sign language translator. Subsequently, the preliminary experimental results show the usefulness of the accelerometer and flex sensors. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-72550-5_34 | RECENT ADVANCES ON SOFT COMPUTING AND DATA MINING (SCDM 2018) |
Keywords | Field | DocType |
Sign language translator,Accelerometer,Flex sensor,Experiment | Conversation,Flex sensor,Computer science,Accelerometer,FLEX,Human–computer interaction,Sign language,Artificial intelligence,Machine learning | Conference |
Volume | ISSN | Citations |
700 | 2194-5357 | 0 |
PageRank | References | Authors |
0.34 | 2 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Radzi Bin Ambar | 1 | 1 | 2.09 |
| Chan Kar Fai | 2 | 0 | 0.34 |
| Chew Chang Choon | 3 | 0 | 0.34 |
| Mohd Helmy Abd Wahab | 4 | 0 | 1.69 |
| M. Mahadi Abdul Jamil | 5 | 3 | 3.23 |
| Ahmad Alabqari Ma'Radzi | 6 | 0 | 0.34 |