语言韵律和情感在字幕中的可视化:聋人和听力障碍者的可及性

Caluã de Lacerda Pataca, Matthew Watkins, Roshan Peiris, Sooyeon Lee, Matt Huenerfauth
{"title":"语言韵律和情感在字幕中的可视化:聋人和听力障碍者的可及性","authors":"Caluã de Lacerda Pataca, Matthew Watkins, Roshan Peiris, Sooyeon Lee, Matt Huenerfauth","doi":"10.1145/3544548.3581511","DOIUrl":null,"url":null,"abstract":"Speech is expressive in ways that caption text does not capture, with emotion or emphasis information not conveyed. We interviewed eight Deaf and Hard-of-Hearing (dhh) individuals to understand if and how captions’ inexpressiveness impacts them in online meetings with hearing peers. Automatically captioned speech, we found, lacks affective depth, lending it a hard-to-parse ambiguity and general dullness. Interviewees regularly feel excluded, which some understand is an inherent quality of these types of meetings rather than a consequence of current caption text design. Next, we developed three novel captioning models that depicted, beyond words, features from prosody, emotions, and a mix of both. In an empirical study, 16 dhh participants compared these models with conventional captions. The emotion-based model outperformed traditional captions in depicting emotions and emphasis, with only a moderate loss in legibility, suggesting its potential as a more inclusive design for captions.","PeriodicalId":314098,"journal":{"name":"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems","volume":"109 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Visualization of Speech Prosody and Emotion in Captions: Accessibility for Deaf and Hard-of-Hearing Users\",\"authors\":\"Caluã de Lacerda Pataca, Matthew Watkins, Roshan Peiris, Sooyeon Lee, Matt Huenerfauth\",\"doi\":\"10.1145/3544548.3581511\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Speech is expressive in ways that caption text does not capture, with emotion or emphasis information not conveyed. We interviewed eight Deaf and Hard-of-Hearing (dhh) individuals to understand if and how captions’ inexpressiveness impacts them in online meetings with hearing peers. Automatically captioned speech, we found, lacks affective depth, lending it a hard-to-parse ambiguity and general dullness. Interviewees regularly feel excluded, which some understand is an inherent quality of these types of meetings rather than a consequence of current caption text design. Next, we developed three novel captioning models that depicted, beyond words, features from prosody, emotions, and a mix of both. In an empirical study, 16 dhh participants compared these models with conventional captions. The emotion-based model outperformed traditional captions in depicting emotions and emphasis, with only a moderate loss in legibility, suggesting its potential as a more inclusive design for captions.\",\"PeriodicalId\":314098,\"journal\":{\"name\":\"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems\",\"volume\":\"109 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3544548.3581511\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3544548.3581511","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

言语的表达方式是文字标题无法捕捉到的,它带有情感或强调信息,无法传达。我们采访了8位聋人和听力障碍者(dhh),以了解字幕的缺乏表达是否以及如何影响他们与听力障碍者的在线会议。我们发现,自动配字幕的演讲缺乏情感深度,导致难以解析的模糊性和普遍的沉闷。受访者经常感到被排除在外,有些人认为这是这些类型会议的固有品质,而不是当前标题文本设计的结果。接下来,我们开发了三种新的字幕模型,除了文字之外,还描述了韵律、情感和两者的混合特征。在一项实证研究中,16名dhh参与者将这些模型与传统字幕进行了比较。基于情感的模型在描述情感和强调方面优于传统的字幕,仅在易读性上有适度的损失,这表明它有潜力成为更具包容性的字幕设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Visualization of Speech Prosody and Emotion in Captions: Accessibility for Deaf and Hard-of-Hearing Users
Speech is expressive in ways that caption text does not capture, with emotion or emphasis information not conveyed. We interviewed eight Deaf and Hard-of-Hearing (dhh) individuals to understand if and how captions’ inexpressiveness impacts them in online meetings with hearing peers. Automatically captioned speech, we found, lacks affective depth, lending it a hard-to-parse ambiguity and general dullness. Interviewees regularly feel excluded, which some understand is an inherent quality of these types of meetings rather than a consequence of current caption text design. Next, we developed three novel captioning models that depicted, beyond words, features from prosody, emotions, and a mix of both. In an empirical study, 16 dhh participants compared these models with conventional captions. The emotion-based model outperformed traditional captions in depicting emotions and emphasis, with only a moderate loss in legibility, suggesting its potential as a more inclusive design for captions.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Characterizing the Technology Needs of Vulnerable Populations for Participation in Research and Design by Adopting Maslow’s Hierarchy of Needs Playing with Power Tools: Design Toolkits and the Framing of Equity "It’s like With the Pregnancy Tests": Co-design of Speculative Technology for Public HIV-related Stigma and its Implications for Social Media Potential and Challenges of DIY Smart Homes with an ML-intensive Camera Sensor Understanding People’s Concerns and Attitudes Toward Smart Cities
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1