activity
20162023
most citedMaking Mobile Augmented Reality Applications Accessible

46 citations · 134 across the 9 of their papers we have counts for

collaborators

10 papers

cs.HC2023

GenAssist: Making Image Generation Accessible

Mina Huh, Yi-Hao Peng, Amy Pavel

Blind and low vision (BLV) creators use images to communicate with sighted audiences. However, creating or retrieving images is challenging for BLV creators as it is difficult to u…

cs.HC2023★ 44 cited

AVscript: Accessible Video Editing with Audio-Visual Scripts

Mina Huh, Saelyne Yang, Yi-Hao Peng +3

Sighted and blind and low vision (BLV) creators alike use videos to communicate with broad audiences. Yet, video editing remains inaccessible to BLV creators. Our formative study r…

cs.HC2022★ 24 cited

CrossA11y: Identifying Video Accessibility Issues via Cross-modal Grounding

Xingyu "Bruce" Liu, Ruolin Wang, Dingzeyu Li +2

Authors make their videos visually accessible by adding audio descriptions (AD), and auditorily accessible by adding closed captions (CC). However, creating AD and CC is challengin…

cs.HC2021★ 2 cited

Say It All: Feedback for Improving Non-Visual Presentation Accessibility

Yi-Hao Peng, JiWoong Jang, Jeffrey P. Bigham +1

Presenters commonly use slides as visual aids for informative talks. When presenters fail to verbally describe the content on their slides, blind and visually impaired audience mem…

cs.HC2020★ 46 cited

Making Mobile Augmented Reality Applications Accessible

Jaylin Herskovitz, Jason Wu, Samuel White +4

Augmented Reality (AR) technology creates new immersive experiences in entertainment, games, education, retail, and social media. AR content is often primarily visual and it is cha…

cs.HC2020★ 1 cited

Rescribe: Authoring and Automatically Editing Audio Descriptions

Amy Pavel, Gabriel Reyes, Jeffrey P. Bigham

Audio descriptions make videos accessible to those who cannot see them by describing visual content in audio. Producing audio descriptions is challenging due to the synchronous nat…

cs.CL2020

Controlling Dialogue Generation with Semantic Exemplars

Prakhar Gupta, Jeffrey P. Bigham, Yulia Tsvetkov +1

Dialogue systems pretrained with large language models generate locally coherent responses, but lack the fine-grained control over responses necessary to achieve specific goals. A…

cs.LG2020★ 1 cited

Extracting Structured Data from Physician-Patient Conversations By Predicting Noteworthy Utterances

Kundan Krishna, Amy Pavel, Benjamin Schloss +2

Despite diverse efforts to mine various modalities of medical data, the conversations between physicians and patients at the time of care remain an untapped source of insights. In…

cs.CL2019

Investigating Evaluation of Open-Domain Dialogue Systems With Human Generated Multiple References

Prakhar Gupta, Shikib Mehri, Tiancheng Zhao +3

The aim of this paper is to mitigate the shortcomings of automatic evaluation of open-domain dialog systems through multi-reference evaluation. Existing metrics have been shown to…

cs.CV2016★ 16 cited

How do people explore virtual environments?

Vincent Sitzmann, Ana Serrano, Amy Pavel +4

Understanding how people explore immersive virtual environments is crucial for many applications, such as designing virtual reality (VR) content, developing new compression algorit…