ELMI: Interactive and Intelligent Sign Language Translation of Lyrics for Song Signing

Suhyeon Yoo, Khai N. Truong, Young-Ho Kim
{"title":"ELMI: Interactive and Intelligent Sign Language Translation of Lyrics for Song Signing","authors":"Suhyeon Yoo, Khai N. Truong, Young-Ho Kim","doi":"arxiv-2409.09760","DOIUrl":null,"url":null,"abstract":"d/Deaf and hearing song-signers become prevalent on video-sharing platforms,\nbut translating songs into sign language remains cumbersome and inaccessible.\nOur formative study revealed the challenges song-signers face, including\nsemantic, syntactic, expressive, and rhythmic considerations in translations.\nWe present ELMI, an accessible song-signing tool that assists in translating\nlyrics into sign language. ELMI enables users to edit glosses line-by-line,\nwith real-time synced lyric highlighting and music video snippets. Users can\nalso chat with a large language model-driven AI to discuss meaning, glossing,\nemoting, and timing. Through an exploratory study with 13 song-signers, we\nexamined how ELMI facilitates their workflows and how song-signers leverage and\nreceive an LLM-driven chat for translation. Participants successfully adopted\nELMI to song-signing, with active discussions on the fly. They also reported\nimproved confidence and independence in their translations, finding ELMI\nencouraging, constructive, and informative. We discuss design implications for\nleveraging LLMs in culturally sensitive song-signing translations.","PeriodicalId":501541,"journal":{"name":"arXiv - CS - Human-Computer Interaction","volume":"3 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Human-Computer Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.09760","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

d/Deaf and hearing song-signers become prevalent on video-sharing platforms, but translating songs into sign language remains cumbersome and inaccessible. Our formative study revealed the challenges song-signers face, including semantic, syntactic, expressive, and rhythmic considerations in translations. We present ELMI, an accessible song-signing tool that assists in translating lyrics into sign language. ELMI enables users to edit glosses line-by-line, with real-time synced lyric highlighting and music video snippets. Users can also chat with a large language model-driven AI to discuss meaning, glossing, emoting, and timing. Through an exploratory study with 13 song-signers, we examined how ELMI facilitates their workflows and how song-signers leverage and receive an LLM-driven chat for translation. Participants successfully adopted ELMI to song-signing, with active discussions on the fly. They also reported improved confidence and independence in their translations, finding ELMI encouraging, constructive, and informative. We discuss design implications for leveraging LLMs in culturally sensitive song-signing translations.
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
ELMI:歌曲手语歌词的交互式智能手语翻译
我们的形成性研究揭示了歌曲手语者所面临的挑战,包括翻译中的语义、句法、表达和节奏方面的考虑。ELMI 使用户能够逐行编辑词汇,并实时同步歌词高亮和音乐视频片段。用户还可以与大型语言模型驱动的人工智能聊天,讨论含义、词汇、情感和时机。通过对 13 位歌曲署名者的探索性研究,我们考察了 ELMI 如何促进他们的工作流程,以及歌曲署名者如何利用和接收 LLM 驱动的聊天翻译。参与者成功地将 ELMI 应用到了歌曲翻译中,并进行了积极的即时讨论。他们还报告说,他们在翻译中的自信心和独立性都得到了提高,并发现 ELMI 具有鼓励性、建设性和信息性。我们讨论了在文化敏感的歌曲签名翻译中利用 LLM 的设计意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Equimetrics -- Applying HAR principles to equestrian activities AI paintings vs. Human Paintings? Deciphering Public Interactions and Perceptions towards AI-Generated Paintings on TikTok From Data Stories to Dialogues: A Randomised Controlled Trial of Generative AI Agents and Data Storytelling in Enhancing Data Visualisation Comprehension Exploring Gaze Pattern in Autistic Children: Clustering, Visualization, and Prediction Revealing the Challenge of Detecting Character Knowledge Errors in LLM Role-Playing
×
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