Typist Experiment: an Investigation of Human-to-Human Dictation via Role-play to Inform Voice-based Text Authoring
<|reference_start|>Typist Experiment: an Investigation of Human-to-Human Dictation via Role-play to Inform Voice-based Text Authoring: Voice dictation is increasingly used for text entry, especially in mobile scenarios. However, the speech-based experience gets disrupted when users must go back to a screen and keyboard to review and edit the text. While existing dictation systems focus on improving transcription and error correction, little is known about how to support speech input for the entire text creation process, including composition, reviewing and editing. We conducted an experiment in which ten pairs of participants took on the roles of authors and typists to work on a text authoring task. By analysing the natural language patterns of both authors and typists, we identified new challenges and opportunities for the design of future dictation interfaces, including the ambiguity of human dictation, the differences between audio-only and with screen, and various passive and active assistance that can potentially be provided by future systems.<|reference_end|>
@article{liu2024typist,
    title={Typist Experiment: an Investigation of Human-to-Human Dictation via
  Role-play to Inform Voice-based Text Authoring},
    author={Can Liu, Siying Hu, Li Feng, Mingming Fan},
    journal={Proc. ACM Hum.-Comput. Interact. 6, CSCW2, Article 338 (November
  2022), 33 pages},
    year={2024},
    doi={10.1145/3555758},
    archivePrefix={arXiv},
    eprint={2403.05785},
    primaryClass={cs.HC}
}