Wearable-tech glove translates sign language into speech in real time
The device is inexpensive, flexible and highly durable

Date:
June 29, 2020
Source:
University of California - Los Angeles
Summary:
Bioengineers have designed a glove-like device that can translate
American Sign Language into English speech in real time though a
smartphone app. The system includes a pair of gloves with thin,
stretchable sensors that run the length of each of the five fingers.

These sensors, made from electrically conducting yarns, pick up hand
motions and finger placements that stand for individual letters,
numbers, words and phrases.



FULL STORY ==========================================================================
UCLA bioengineers have designed a glove-like device that can translate
American Sign Language into English speech in real time though a
smartphone app. Their research is published in the journal Nature
Electronics.


==========================================================================
"Our hope is that this opens up an easy way for people who use sign
language to communicate directly with non-signers without needing someone
else to translate for them," said Jun Chen, an assistant professor
of bioengineering at the UCLA Samueli School of Engineering and the
principal investigator on the research.

"In addition, we hope it can help more people learn sign language
themselves." The system includes a pair of gloves with thin, stretchable sensors that run the length of each of the five fingers. These sensors,
made from electrically conducting yarns, pick up hand motions and finger placements that stand for individual letters, numbers, words and phrases.

The device then turns the finger movements into electrical signals, which
are sent to a dollar-coin-sized circuit board worn on the wrist. The
board transmits those signals wirelessly to a smartphone that translates
them into spoken words at the rate of about a one word per second.

The researchers also added adhesive sensors to testers' faces -- in
between their eyebrows and on one side of their mouths -- to capture
facial expressions that are a part of American Sign Language.

Previous wearable systems that offered translation from American
Sign Language were limited by bulky and heavy device designs or were uncomfortable to wear, Chen said.

The device developed by the UCLA team is made from lightweight and
inexpensive but long-lasting, stretchable polymers. The electronic
sensors are also very flexible and inexpensive.

In testing the device, the researchers worked with four people who
are deaf and use American Sign Language. The wearers repeated each
hand gesture 15 times. A custom machine-learning algorithm turned these gestures into the letters, numbers and words they represented. The system recognized 660 signs, including each letter of the alphabet and numbers
0 through 9.


========================================================================== Story Source: Materials provided by
University_of_California_-_Los_Angeles. Note: Content may be edited for
style and length.


========================================================================== Journal Reference:
1. Zhihao Zhou, Kyle Chen, Xiaoshi Li, Songlin Zhang, Yufen Wu,
Yihao Zhou,
Keyu Meng, Chenchen Sun, Qiang He, Wenjing Fan, Endong
Fan, Zhiwei Lin, Xulong Tan, Weili Deng, Jin Yang & Jun
Chen. Sign-to-speech translation using machine-learning-assisted
stretchable sensor arrays. Nature Electronics, 2020 DOI:
http://dx.doi.org/10.1038/s41928-020-0428-6 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/06/200629120201.htm

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