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An exploratory study (N=3) further demonstrates editing by BLV creators of their own 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problem does AVscript address for BLV video creators?","Question",{"text":62,"@type":63},"It addresses the inaccessibility of video editing for blind and low vision creators, where current tools require visual inspection to find edit points and assess visual quality.","Answer",{"name":65,"@type":60,"acceptedAnswer":66},"How does AVscript support editing in a text-based way?",{"text":67,"@type":63},"AVscript uses an audio-visual script segmented by scenes, including scene descriptions and highlighted visual errors (e.g., blur and bad lighting), enabling navigation between scenes and errors.",{"name":69,"@type":60,"acceptedAnswer":70},"What evidence is provided to evaluate AVscript?",{"text":71,"@type":63},"A comparison study with N=12 BLV creators shows lower mental demand and higher confidence and independence, and an exploratory study with N=3 demonstrates editing of their own 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USA [minahuh@cs.utexas.edu](minahuh@cs.utexas.edu)  \nXiang ‘Anthony’ Chen  \nUCLA Los Angeles, CA, USA [xac@ucla.edu](xac@ucla.edu)  \nSaelyne Yang  \nKAIST Daejeon, Republic of Korea  \n[saelyne@kaist.ac.kr](saelyne@kaist.ac.kr)  \nYoung-Ho Kim  \nNAVER AI Lab Republic of Korea [yghokim@younghokim.net](yghokim@younghokim.net)  \nYi-Hao Peng  \nCarnegie Mellon University Pittsburgh, PA, USA [yihaop@cs.cmu.edu](yihaop@cs.cmu.edu)  \nAmy Pavel  \nThe University of Texas at Austin Austin, TX, USA [apavel@cs.utexas.edu](apavel@cs.utexas.edu)  \nA. Video pane  \nD. Tool pane  \nE. Search Pane  \nSearch 0 of 0  \nCamera blur: And in my pantry.  \nPause: 25.5 seconds  \nbut I just have things kind of organized  \nBad lighting: So I’ll just show it to you here  \nB. Script Pane  \nFigure 1: AVscript is an accessible text-based video editing tool that enables blind and low vision (BLV) creators to edit videos efficiently using a screen reader. The video pane (A) provides notifications for visual errors and supports inspection of visual objects. The script pane (B) provides a narration transcript segmented by scenes, scene descriptions, and highlighted visual errors (e.g., blur, bad lighting). The outline pane (C) a navigable summary of the video scenes and errors. The tool pane (D) allows users to change the playback speed or trim of a selected video clip. The search pane (E) supports both visual search and narration search of the video.  \nABSTRACT  \nSighted and blind and low vision (BLV) creators alike use videos to communicate with broad audiences. Yet, video editing remains inaccessible to BLV creators. Our formative study revealed that current video editing tools make it difficult to access the visual content,  \n∗ Mina Huh conducted part of this work as a research intern at NAVER AI Lab.  \nPermission to make digital or hard copies of part or all ofthis 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(s) .  \nCHI’23, April 23–28, 2023, Hamburg, Germany © 2023 Copyright held by the owner/author(s) .  \nACM ISBN 978-1-4503-9421-5/23/04 .  \n[https://doi.org/10.1145/3544548.3581494](https://doi.org/10.1145/3544548.3581494)  \nassess the visual quality, and efficiently navigate the timeline. We present AVscript, an accessible text-based video editor. AVscript enables BLV creators to edit their video using a script that embeds the video’s visual content, visual errors (e.g., dark or blurred footage), and speech. BLV creators can use AVscript to efficiently navigate between scenes and visual errors or to locate objects in the frame or spoken words of interest. A comparison study (N=12) showed that AVscript significantly lowered BLV creators’ mental demand while increasing confidence and independence in video editing. We further demonstrate the potential of AVscript through an exploratory study (N=3) where BLV creators edited their own footage.  \nCHI ’23, April 23–28, 2023, Hamburg, Germany Mina Huh, Saelyne Yang, Yi-Hao Peng, Xiang ‘Anthony’ Chen, Young-Ho Kim, and Amy Pavel  \nCCS CONCEPTS  \n• Human-centered computing; • Accessibility systems and tools;  \nKEYWORDS  \nvideo, authoring tools, accessibility  \nACM Reference Format:  \nMina Huh, Saelyne Yang, Yi-Hao Peng, Xiang ‘Anthony’ Chen, Young-Ho Kim, and Amy Pavel. 2023. AVscript: Accessible Video Editing with AudioVisual Scripts. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI’23), April 23–28, 2023, Hamburg, Germany. ACM, New York, NY, USA, 17 pages. [https://doi.org/10.1145/3544548.3581494](https://doi.org/10.1145/3544548.3581494)  \n1 INTRODUCTION  \nPeople create videos to share th","cbCaijjz4EcFz6Rj","https://ap.wps.com/l/cbCaijjz4EcFz6Rj","pdf",1344035,17,"English","# Introduction\n## Problem: inaccessible video editing for BLV creators\n## Overview of AVscript\n## Study design and results","[{\"question\":\"What problem does AVscript address for BLV video creators?\",\"answer\":\"It addresses the inaccessibility of video editing for blind and low vision creators, where current tools require visual inspection to find edit points and assess visual quality.\"},{\"question\":\"How does AVscript support editing in a text-based way?\",\"answer\":\"AVscript uses an audio-visual script segmented by scenes, including scene descriptions and highlighted visual errors (e.g., blur and bad lighting), enabling navigation between scenes and errors.\"},{\"question\":\"What evidence is provided to evaluate AVscript?\",\"answer\":\"A comparison study with N=12 BLV creators shows lower mental demand and higher confidence and independence, and an exploratory study with N=3 demonstrates editing of their own footage.\"}]","AVscript - Accessible Video Editing with Audio-Visual Scripts | PDF",1790644333,43]