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Exploring Motor-impaired Programmers’ Use of Speech Recognition

Published: 22 October 2022 Publication History

Abstract

Typing programs can be difficult or impossible for programmers with motor impairments. Programming by voice can be a promising alternative. In this research, we explored the perceptions of motor-impaired programmers with regard to programming by voice. We learned that leveraging existing voice-based programming platforms to speak code can be more complicated than it needs to be. The interviewees expressed their frustration with long hours of memorizing unnatural commands in order to enter code by voice. In addition, we found a preference for being able to speak code in a flexible manner without requiring strict adherence to a grammar.

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Cited By

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  • (2024)Leveraging Large Pretrained Models for Line-by-Line Spoken Program RecognitionICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP48485.2024.10448435(12216-12220)Online publication date: 14-Apr-2024
  • (2023)Programming by Voice: Exploring User Preferences and Speaking StylesProceedings of the 5th International Conference on Conversational User Interfaces10.1145/3571884.3597130(1-13)Online publication date: 19-Jul-2023

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  1. Exploring Motor-impaired Programmers’ Use of Speech Recognition

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    cover image ACM Conferences
    ASSETS '22: Proceedings of the 24th International ACM SIGACCESS Conference on Computers and Accessibility
    October 2022
    902 pages
    ISBN:9781450392587
    DOI:10.1145/3517428
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Publication History

    Published: 22 October 2022

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    Author Tags

    1. Accessibility
    2. Speech Recognition
    3. Voice Programming
    4. Voice User Interfaces

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    ASSETS '22 Paper Acceptance Rate 35 of 132 submissions, 27%;
    Overall Acceptance Rate 436 of 1,556 submissions, 28%

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    • (2024)Leveraging Large Pretrained Models for Line-by-Line Spoken Program RecognitionICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP48485.2024.10448435(12216-12220)Online publication date: 14-Apr-2024
    • (2023)Programming by Voice: Exploring User Preferences and Speaking StylesProceedings of the 5th International Conference on Conversational User Interfaces10.1145/3571884.3597130(1-13)Online publication date: 19-Jul-2023

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