Research has observed benefits from providing lexical and syntactic approaches to Automatic Text Simplification (ATS) to Deaf and Hard-of-hearing (DHH) readers. However, little research has explored DHH readers’ design preferences and interactions with these approaches. This work first explores the design space of ATS systems with DHH readers, identifying potential design configurations for evaluation. Open-ended discussion of participants’ design preferences reveal values informing those preferences, including maintaining reading fluency and efficiency, and control over the tool. Using popular design choices from our formative study, we evaluated a prototype that provides various simplification types to explore DHH readers’ interactions with the system. We observed potential conflicts between participants’ values and design preferences, such as the prototype’s impact on participants’ reading speed and participants’ perceived need to reread simplifications suggested by the tool. However, participants found the tool useful, showing a nuanced preference towards world-level lexical simplifications using pop-ups. Our findings highlight the importance of the tool’s design on users’ reading experiences, and provide implications for the design and evaluation of ATS prototypes with target readers.

As they develop comprehension skills, American Sign Language (ASL) learners often view challenging ASL videos, which may contain unfamiliar signs. Current dictionary tools require students to isolate a single sign they do not understand and input a search query, by selecting linguistic properties or by performing the sign into a webcam. Students may struggle with extracting and re-creating an unfamiliar sign, and they must leave the video-watching task to use an external dictionary tool. We investigate a technology that enables users, in the moment, i.e., while they are viewing a video, to select a span of one or more signs that they do not understand, to view dictionary results. We interviewed 14 American Sign Language (ASL) learners about their challenges in understanding ASL video and workarounds for unfamiliar vocabulary. We then conducted a comparative study and an in-depth analysis with 15 ASL learners to investigate the benefits of using video sub-spans for searching, and their interactions with a Wizard-of-Oz prototype during a video-comprehension task. Our findings revealed benefits of our tool in terms of quality of video translation produced and perceived workload to produce translations. Our in-depth analysis also revealed benefits of an integrated search tool and use of span-selection to constrain video play. These findings inform future designers of such systems, computer vision researchers working on the underlying sign matching technologies, and sign language educators.

Television captions blocking visual information causes dissatisfaction among Deaf and Hard of Hearing (DHH) viewers, yet existing caption evaluation metrics do not consider occlusion. To create such a metric, DHH participants in a recent study imagined how bad it would be if captions blocked various on-screen text or visual content. To gather more ecologically valid data for creating an improved metric, we asked 24 DHH participants to give subjective judgments of caption quality after actually watching videos, and a regression analysis revealed which on-screen contents’ occlusion related to users’ judgments. For several video genres, a metric based on our new dataset out-performed the prior state-of-the-art metric for predicting the severity of captions occluding content during videos, which had been based on that prior study. We contribute empirical findings for improving DHH viewers’ experience, guiding the placement of captions to minimize occlusions, and automated evaluation of captioning quality in television broadcasts.

Searching for the meaning of an unfamiliar sign-language word in a dictionary is difficult for learners, but emerging sign-recognition technology will soon enable users to search by submitting a video of themselves performing the word they recall. However, sign-recognition technology is imperfect, and users may need to search through a long list of possible results when seeking a desired result. To speed this search, we present a hybrid-search approach, in which users begin with a video-based query and then filter the search results by linguistic properties, e.g., handshape. We interviewed 32 ASL learners about their preferences for the content and appearance of the search-results page and filtering criteria. A between-subjects experiment with 20 ASL learners revealed that our hybrid search system outperformed a video-based search system along multiple satisfaction and performance metrics. Our findings provide guidance for designers of video-based sign-language dictionary search systems, with implications for other search scenarios.