Christian Vogler

schoolGallaudet Universitybar_chart#2856 Global Rank

Total Papers

HCI Rank

#2856

Research Areas

Years Active

Recent Publications

Deaf and Hard of Hearing Access to Intelligent Personal Assistants: Comparison of Voice-Based Options with an LLM-Powered Touch Interface

We investigate intelligent personal assistants (IPAs) accessibility for deaf and hard of hearing (DHH) people who can use their voice in everyday communication. The inability of IPAs to understand diverse accents including deaf speech renders them largely inaccessible to non-signing and speaking DHH individuals. Using…

CHI '244th AuthorDeaf & Hard-of-Hearing Support (Captions, Sign Language, Vibration) +2

Towards Co-Creating Access and Inclusion: A Group Autoethnography on a Hearing Individual's Journey Towards Effective Communication in Mixed-Hearing Ability Higher Education Settings

We present a group autoethnography detailing a hearing student's journey in adopting communication technologies at a mixed-hearing ability summer research camp. Our study focuses on how this student, a research assistant with emerging American Sign Language (ASL) skills, (in)effectively communicates with deaf and hard…

CHI '24CorrespondingIntelligent Voice Assistants (Alexa, Siri, etc.) +1

Assessment of Sign Language-Based versus Touch-Based Input for Deaf Users Interacting with Intelligent Personal Assistants

With the recent advancements in intelligent personal assistants (IPAs), their popularity is rapidly increasing when it comes to utilizing Automatic Speech Recognition within households. In this study, we used a Wizard-of-Oz methodology to evaluate and compare the usability of American Sign Language (ASL), Tap to Alexa…

CHI '24CorrespondingHonorable MentionVoice Accessibility +2

How Users Experience Closed Captions on Live Television: Quality Metrics Remain a Challenge

This paper presents a mixed methods study on how deaf, hard of hearing and hearing viewers perceive live TV caption quality with captioned video stimuli designed to mirror TV captioning experiences. To assess caption quality, we used four commonly-used quality metrics focusing on accuracy: word error rate, weighted wo…

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