{"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.
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。