Helen: An Intelligent Virtual Assistant for People with Auditory Problems

The integration of artificial intelligence has grown exponentially to improve human interaction with the world. The most common examples are virtual assistants such as Alexa, Siri, Cortana, or Google, and electronic devices that can connect with other electronic devices in the home. Undoubtedly, incorporating these virtual assistants and devices has supported and improved the interaction of users with low technological experience or people with a motor impairment who can also benefit from them. However, people with auditory problems who are commonly limited verbally and use sign language to communicate can not use virtual assistants in their current design. Therefore, some authors have pointed out the importance of developing devices and creating environments so that people with auditory disability can improve their interaction with these devices. Hence, this study aims to introduce Helen, a virtual assistant for people with auditory disability. Its design is based on a qualitative analysis of semi-structured interviews with people with auditory problems. Helen can perform some actions using sign language. This study presents the results of the interviews, the details of Helen's design, the hardware construction, and the user interface design. We firmly believe this project will serve as a cornerstone for empowering the deaf community, providing them with a virtual assistant to control various home devices.

Authors

Publication Details

Published
2024-10-28
DOI
https://doi.org/10.1109/conisoft63288.2024.00046
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Helen: An Intelligent Virtual Assistant for People with Auditory Problems

Samantha Jiménez, Camilo Caraveo, Leticia Cervantes, Mario Sánchez Aguilar et al.
Context-Aware Activity Recognition Systems
article

Helen: An Intelligent Virtual Assistant for People with Auditory Problems

Samantha Jiménez, Camilo Caraveo, Leticia Cervantes, Mario Sánchez Aguilar, Fernanda Ugalde G., Mauricio Y. Chávez, Gael H. Durán, Rafael Chávez, Rosemberg Flores
article en

Abstract

The integration of artificial intelligence has grown exponentially to improve human interaction with the world. The most common examples are virtual assistants such as Alexa, Siri, Cortana, or Google, and electronic devices that can connect with other electronic devices in the home. Undoubtedly, incorporating these virtual assistants and devices has supported and improved the interaction of users with low technological experience or people with a motor impairment who can also benefit from them. However, people with auditory problems who are commonly limited verbally and use sign language to communicate can not use virtual assistants in their current design. Therefore, some authors have pointed out the importance of developing devices and creating environments so that people with auditory disability can improve their interaction with these devices. Hence, this study aims to introduce Helen, a virtual assistant for people with auditory disability. Its design is based on a qualitative analysis of semi-structured interviews with people with auditory problems. Helen can perform some actions using sign language. This study presents the results of the interviews, the details of Helen's design, the hardware construction, and the user interface design. We firmly believe this project will serve as a cornerstone for empowering the deaf community, providing them with a virtual assistant to control various home devices.

Openalex Percentile: Top 77%
Context-Aware Activity Recognition Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Helen: An Intelligent Virtual Assistant for People with Auditory Problems — Samantha Jiménez, Camilo Caraveo, et al. · (2024) | TGRS Research Map | TGRS