C. T. Justine Hui

Papers

Total Citations

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About

C. T. Justine Hui is a researcher whose work bridges the fields of speech communication, human-machine interaction, and language processing. Her primary research focuses on how the structural and lexical properties of language affect intelligibility in machine-to-human communications, a critical area for improving voice-based AI systems and assistive technologies. In her most-cited paper, "Effects of sentence structure and word complexity on intelligibility in machine-to-human communications" (2019), Hui systematically examined how syntactic complexity and word difficulty influence how well humans understand synthetic speech. This work has garnered 4 citations, laying a foundation for more accessible and effective human-machine dialogue systems. While her citation count is modest, Hui’s contributions are notable for their practical implications in designing clearer, more natural-sounding synthetic voices—a growing need as voice assistants and automated customer service become ubiquitous. Her research offers valuable insights for developers and linguists alike, highlighting the importance of tailoring language complexity to listener comprehension. Hui’s work stands as a stepping stone for future studies on optimizing communication between humans and machines.