Donna Easton

Deaf/Hard of Hearing and Other Postsecondary Learners' Retention of STEM Content With Tablet Computer-Based Notes

Four groups of postsecondary students, 25 who were deaf/hard of hearing (D/HH), 25 with a learning disability, 25 who were English language learners (ELLs), and 25 without an identified disability studied notes that included text and graphical information based on a physics or a marine biology lecture. The latter 3 groups were normally hearing. All groups had higher scores on post- than on pretests for each lecture, with each group showing generally similar gains in amount of material learned from the pretest to the posttest. For each lecture, the D/HH students scored lower on the pre- and posttests than the other 3 groups of participants. Results indicated that students acquired measurable amounts of information from studying these types of notes for relatively short periods and that the notes have equal potential to support the acquisition of information by each of these groups of students.

Real-time caption challenge: C-print

This poster/demonstration session showcases C-Print, a typing-based transcription system. This form of real-time captioning will be provided for approximately one half day during the ASSETS 2014 Conference and will be part of a real-time caption challenge. The C-Print system requires a trained transcriptionist who uses computerized abbreviations and condensing strategies to produce the text display of spoken information. This spoken information appears as text on a computer or mobile device for viewing by the consumer approximately two seconds later.

User Experiences When Testing a Messaging App for Communication Between Individuals who are Hearing and Deaf or Hard of Hearing

This study investigated user experiences of participants testing a prototype messaging app with automatic speech recognition (ASR). Twelve pairs of participants, where one individual was deaf or hard-of-hearing (DHH), and the other one was hearing used the app, with the hearing individual using speech and ASR and the DHH one using typing. Participants completed a standardized decision making task to test the app. Regardless of hearing status of the participants or the type of device used, participants were generally satisfied with the app. These findings indicate that ASR has potential to facilitate communication between DHH and hearing individuals in small groups and that the technology merits further investigation.

Personal Perspectives on Using Automatic Speech Recognition to Facilitate Communication between Deaf Students and Hearing Customers

Automatic Speech Recognition (ASR) and the wide use of smart phones and their apps have allowed huge inroads when preparing deaf and hard-of-hearing (D/HH) students to be effective and productive in the hearing workplace. This paper presents both a hearing instructors experiences and a deaf researchers observations when preparing deaf and hard of hearing students as computer technicians for the hearing work place.

Using Automatic Speech Recognition to Facilitate Communication Between an Individual who is Hearing and One who is Deaf or Hard of Hearing

This study investigated use of automatic speech recognition (ASR) in 12 pairs where one individual was deaf or hard-of-hearing (DHH), and the other one was hearing, with the hearing individual using speech and ASR and the DHH one using typing. Each of the pairs used prototype software for messaging to communicate while completing a standardized decision making task. Results suggested that ASR produced text at a faster rate than a keyboard. When both participants used keyboards, they exchanged more messages than when one or both of them used a smartphone with a miniature keyboard.