Klingo: Community-sourcing Image-based Q&A for Translation and Local Knowledge Sharing

Foreigners who travel or live in countries whose languages use non-alphanumeric characters require significant help for language translation and local information (e.g. posters, signs, directions). We first identify major breakdowns of image-based Q&A by studying Q&A interactions between foreign askers and local answerers. We then design Klingo, a mobile Q&A platform that allows foreigners to ask image-based questions to a local community of native speakers for language translation and local knowledge sharing. The results of our initial field study show that, by facilitating collaborative interactions among foreign askers and local answerers, Klingo has enabled askers to get more information through follow-up questions and answerers to provide better answers by building on top of other people’s responses.

For more details, you can read the full paper here.

Contribution & Tech Stack

Klingo was a term project for KSE 652 (Social Computing under Prof. Uichin Lee) during the Fall Semester 2016. I was responsible for the design and implementation of the formative study, prototyping, and user evaluation as described in the paper. The interface for both korean and foreigner users was implemented in Android. Firebase was used for most of the application's backend. The image editing and annotation feature was achieved through the integration of imgly's PhotoEditor SDK . We submitted this project to CHI 2017 Late Breaking Work, but it has been rejected.

The Prototype