2024 | Student

MUSE Design Awards Silver Winner

E-sync

Entrant

Tsinghua University, Central Academey of Fine Arts, University of Science and Technology Beijing, Beijing University of Posts and Telecommunications

Category

Product Design - Wearable Technologies

Client's Name

Siqi Wang, Wenfei Li, Yiyu Qi, Wenbing Du, Yihuan Ma

Country / Region

China

Gallery

About The Entry

Currently, people with hearing impairments mainly rely on sign language and written communication to interact with others, which limits their access to auditory cues such as tone of voice. This means they are unable to fully grasp the concept of “emotions” during social interactions, leading to communication barriers and difficulties in social adaptation. However, existing communication products in the market for the hearing impaired mostly focus on converting others’ language into text, without helping them understand “intonation” or better express their own emotions. E-sync is dedicated to enabling people with severe hearing loss, profound hearing loss and complete hearing loss to understand and express emotions, optimizing the communication process between the hearing impaired and normal hearing people, thus helping them integrate into society more efficiently. To address the issue that the hearing impaired can’t comprehend other’s emotion, E-sync converts people’s audio signals into visual and tactile signals for the user. When users wear E-sync, AI will recognize the language and tone of the conversation partner, convert them into text. E-sync will display them in front of the user. Additionally, it can also analyzes semanteme of the text and convert them into distinct vibration frequencies. On the other hand, to solve the problem of efficient expression,E-sync converts hearing impaired’s visual signals and physiological information to audio signals. It firstly asks the user to select a social situation, and during the communication process, uses camera to identify hearing impaired‘s sign language. These information are then processed by AI and transformed into appropriate voice information for the chosen social situation.

Credits

Tsinghua University
Siqi Wang
Central Academey of Fine Arts
Wenfei Li
Central Academey of Fine Arts
Yiyu Qi
University of Science and Technology Beijing
Wenbing Du
Beijing University of Posts and Telecommunications
Yihuan Ma
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