ISeee Project: Information Support of Everyone, by Everyone, for Everyone
What is ISeee Project?
ISeee is an abbreviation of "Information Support of Everyone, by Everyone, for Everyone."
- - Information Support
- - of Everyone
- - by Everyone (Everyone provides information support)
- - for Everyone (Everyone receives information support)
Information support is the technology that helps people with disabilities acquire information using alternative means. ISeee project applies crowdsourcing technique to the field of information support and aims to provide a platform where everyone can make good use of their abilities to provide information support so that everyone can receive information support regardless of disabled or non-disabled people. We expect to realize a society where everyone can say "I see."
As the first step, we are developing a crowdsourcing-based system of sign language captioning by deaf and hard-of-hearing people. Multiple non-expert people who know sign language cooperate to interpret sign language to text in real-time, which provides information support to the people who do not know sign language. One of our goal is to achieve a practical use of the system at academic conventions by the end of fiscal 2017. The constructed system will be open to the public.
- Rumi Hiraga (Tsukuba University of Technology)
- Yuhki Shiraishi (Tsukuba University of Technology)
- Jianwei Zhang (Iwate University)
- Daisuke Wakatsuki (Tsukuba University of Technology)
- Takeaki Shionome
- Katsumi Kumai (University of Tsukuba)
- Hirotaka Hashimoto (University of Tsukuba)
- Atsuyuki Morishima (University of Tsukuba)
- Emi Sakurai (University of Tsukuba, till fiscal 2015)
- Akiko Kawabata (University of Tsukuba, till fiscal 2015)
- Katsumi Kumai, Yuhki Shiraishi, Jianwei Zhang, Hiroyuki Kitagawa and Atsuyuki Morishima,
"Group Rotation Type Crowdsourcing",
The Fourth AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2016), Work-in-Progress Poster, 3 pages, Austin, Texas, USA, November 2016.
- Jianwei Zhang, Yuhki Shiraishi, Katsumi Kumai, and Atsuyuki Morishima,
"Real-Time Captioning of Sign Language by Groups of Deaf and Hard-of-Hearing People",
Proc. The 18th International Conference on Information Integration and Web-based Applications & Services (iiWAS 2016), pp. 56-65, Singapore, November 2016.
- Yuhki Shiraishi, Jianwei Zhang, Daisuke Wakatsuki, Katsumi Kumai, and Atsuyuki Morishima, "Crowdsourced Real-Time Captioning of Sign Language by Deaf and Hard-of-Hearing People", International Journal of Pervasive Computing and Communications, Vol. 13, No. 1, 2017. (forthcoming)
Support Organization / Funding
- This work is partially supported by NII, Tsukuba University of Technology, JST, JSPS.