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Voice and Touch Based Error-tolerant Multimodal Text Editing and Correction for Smartphones

Editing operations such as cut, copy, paste, and correcting errors in typed text are often tedious and challenging to perform on smartphones. In this paper, we present VT, a voice and touch-based multi-modal text editing and correction method for smartphones. To edit text with VT, the user glides ov...

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Detalles Bibliográficos
Autores principales: Zhao, Maozheng, Cui, Wenzhe, Ramakrishnan, I.V., Zhai, Shumin, Bi, Xiaojun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8845054/
https://www.ncbi.nlm.nih.gov/pubmed/35174370
http://dx.doi.org/10.1145/3472749.3474742
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author Zhao, Maozheng
Cui, Wenzhe
Ramakrishnan, I.V.
Zhai, Shumin
Bi, Xiaojun
author_facet Zhao, Maozheng
Cui, Wenzhe
Ramakrishnan, I.V.
Zhai, Shumin
Bi, Xiaojun
author_sort Zhao, Maozheng
collection PubMed
description Editing operations such as cut, copy, paste, and correcting errors in typed text are often tedious and challenging to perform on smartphones. In this paper, we present VT, a voice and touch-based multi-modal text editing and correction method for smartphones. To edit text with VT, the user glides over a text fragment with a finger and dictates a command, such as “bold” to change the format of the fragment, or the user can tap inside a text area and speak a command such as “highlight this paragraph” to edit the text. For text correcting, the user taps approximately at the area of erroneous text fragment and dictates the new content for substitution or insertion. VT combines touch and voice inputs with language context such as language model and phrase similarity to infer a user’s editing intention, which can handle ambiguities and noisy input signals. It is a great advantage over the existing error correction methods (e.g., iOS’s Voice Control) which require precise cursor control or text selection. Our evaluation shows that VT significantly improves the efficiency of text editing and text correcting on smartphones over the touch-only method and the iOS’s Voice Control method. Our user studies showed that VT reduced the text editing time by 30.80%, and text correcting time by 29.97% over the touch-only method. VT reduced the text editing time by 30.81%, and text correcting time by 47.96% over the iOS’s Voice Control method.
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spelling pubmed-88450542022-02-15 Voice and Touch Based Error-tolerant Multimodal Text Editing and Correction for Smartphones Zhao, Maozheng Cui, Wenzhe Ramakrishnan, I.V. Zhai, Shumin Bi, Xiaojun Proc ACM Symp User Interface Softw Tech Article Editing operations such as cut, copy, paste, and correcting errors in typed text are often tedious and challenging to perform on smartphones. In this paper, we present VT, a voice and touch-based multi-modal text editing and correction method for smartphones. To edit text with VT, the user glides over a text fragment with a finger and dictates a command, such as “bold” to change the format of the fragment, or the user can tap inside a text area and speak a command such as “highlight this paragraph” to edit the text. For text correcting, the user taps approximately at the area of erroneous text fragment and dictates the new content for substitution or insertion. VT combines touch and voice inputs with language context such as language model and phrase similarity to infer a user’s editing intention, which can handle ambiguities and noisy input signals. It is a great advantage over the existing error correction methods (e.g., iOS’s Voice Control) which require precise cursor control or text selection. Our evaluation shows that VT significantly improves the efficiency of text editing and text correcting on smartphones over the touch-only method and the iOS’s Voice Control method. Our user studies showed that VT reduced the text editing time by 30.80%, and text correcting time by 29.97% over the touch-only method. VT reduced the text editing time by 30.81%, and text correcting time by 47.96% over the iOS’s Voice Control method. 2021-10 2021-10-12 /pmc/articles/PMC8845054/ /pubmed/35174370 http://dx.doi.org/10.1145/3472749.3474742 Text en https://creativecommons.org/licenses/by-nc-sa/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike International 4.0 License (https://creativecommons.org/licenses/by-nc-sa/4.0/) .
spellingShingle Article
Zhao, Maozheng
Cui, Wenzhe
Ramakrishnan, I.V.
Zhai, Shumin
Bi, Xiaojun
Voice and Touch Based Error-tolerant Multimodal Text Editing and Correction for Smartphones
title Voice and Touch Based Error-tolerant Multimodal Text Editing and Correction for Smartphones
title_full Voice and Touch Based Error-tolerant Multimodal Text Editing and Correction for Smartphones
title_fullStr Voice and Touch Based Error-tolerant Multimodal Text Editing and Correction for Smartphones
title_full_unstemmed Voice and Touch Based Error-tolerant Multimodal Text Editing and Correction for Smartphones
title_short Voice and Touch Based Error-tolerant Multimodal Text Editing and Correction for Smartphones
title_sort voice and touch based error-tolerant multimodal text editing and correction for smartphones
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8845054/
https://www.ncbi.nlm.nih.gov/pubmed/35174370
http://dx.doi.org/10.1145/3472749.3474742
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