@inproceedings{yang-etal-2024-jie,
title = "结合{LLM}与3{D}动画技术的手语数字人系统",
author = "Yang, Yang and
Ying, Zhang and
Kaiyu, Huang and
Jinan, Xu",
editor = "Lin, Hongfei and
Tan, Hongye and
Li, Bin",
booktitle = "Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)",
month = jul,
year = "2024",
address = "Taiyuan, China",
publisher = "Chinese Information Processing Society of China",
url = "https://aclanthology.org/2024.ccl-3.44/",
pages = "393--404",
language = "zho",
abstract = "{\textquotedblleft}手语翻译(Sign Language Translation, SLT)系统作为一种重要的辅助技术,为听障人士提供了与他人沟通的有效途径。然而,传统手语翻译系统在准确性、流畅性差等方面存在问题。本文提出了一种结合大语言模型(Large Language Model, LLM)和3D动画技术(3D Animation Technology)的手语翻译系统,旨在克服这些局限,提高翻译的准确性和流畅性。本文详细介绍了系统的设计与实现过程,包括提示词设计、数据处理方法以及手语数字人翻译系统的实现。实验结果表明,采用LLM方法在手语翻译中能够生成较为自然和准确的结果。在标准评估和人工评估的两种评估方法下,本系统在大多数情况下能够较好地完成手语翻译任务,性能优于传统方法。本文的研究为进一步改进手语翻译系统提供了有益的参考和启示。{\textquotedblright}"
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="yang-etal-2024-jie">
<titleInfo>
<title>结合LLM与3D动画技术的手语数字人系统</title>
</titleInfo>
<name type="personal">
<namePart type="given">Yang</namePart>
<namePart type="family">Yang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Zhang</namePart>
<namePart type="family">Ying</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Huang</namePart>
<namePart type="family">Kaiyu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Xu</namePart>
<namePart type="family">Jinan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2024-07</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<language>
<languageTerm type="text">zho</languageTerm>
</language>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Hongfei</namePart>
<namePart type="family">Lin</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Hongye</namePart>
<namePart type="family">Tan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Bin</namePart>
<namePart type="family">Li</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Chinese Information Processing Society of China</publisher>
<place>
<placeTerm type="text">Taiyuan, China</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>“手语翻译(Sign Language Translation, SLT)系统作为一种重要的辅助技术,为听障人士提供了与他人沟通的有效途径。然而,传统手语翻译系统在准确性、流畅性差等方面存在问题。本文提出了一种结合大语言模型(Large Language Model, LLM)和3D动画技术(3D Animation Technology)的手语翻译系统,旨在克服这些局限,提高翻译的准确性和流畅性。本文详细介绍了系统的设计与实现过程,包括提示词设计、数据处理方法以及手语数字人翻译系统的实现。实验结果表明,采用LLM方法在手语翻译中能够生成较为自然和准确的结果。在标准评估和人工评估的两种评估方法下,本系统在大多数情况下能够较好地完成手语翻译任务,性能优于传统方法。本文的研究为进一步改进手语翻译系统提供了有益的参考和启示。”</abstract>
<identifier type="citekey">yang-etal-2024-jie</identifier>
<location>
<url>https://aclanthology.org/2024.ccl-3.44/</url>
</location>
<part>
<date>2024-07</date>
<extent unit="page">
<start>393</start>
<end>404</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T 结合LLM与3D动画技术的手语数字人系统
%A Yang, Yang
%A Ying, Zhang
%A Kaiyu, Huang
%A Jinan, Xu
%Y Lin, Hongfei
%Y Tan, Hongye
%Y Li, Bin
%S Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)
%D 2024
%8 July
%I Chinese Information Processing Society of China
%C Taiyuan, China
%G zho
%F yang-etal-2024-jie
%X “手语翻译(Sign Language Translation, SLT)系统作为一种重要的辅助技术,为听障人士提供了与他人沟通的有效途径。然而,传统手语翻译系统在准确性、流畅性差等方面存在问题。本文提出了一种结合大语言模型(Large Language Model, LLM)和3D动画技术(3D Animation Technology)的手语翻译系统,旨在克服这些局限,提高翻译的准确性和流畅性。本文详细介绍了系统的设计与实现过程,包括提示词设计、数据处理方法以及手语数字人翻译系统的实现。实验结果表明,采用LLM方法在手语翻译中能够生成较为自然和准确的结果。在标准评估和人工评估的两种评估方法下,本系统在大多数情况下能够较好地完成手语翻译任务,性能优于传统方法。本文的研究为进一步改进手语翻译系统提供了有益的参考和启示。”
%U https://aclanthology.org/2024.ccl-3.44/
%P 393-404
Markdown (Informal)
[结合LLM与3D动画技术的手语数字人系统](https://aclanthology.org/2024.ccl-3.44/) (Yang et al., CCL 2024)
ACL
- Yang Yang, Zhang Ying, Huang Kaiyu, and Xu Jinan. 2024. 结合LLM与3D动画技术的手语数字人系统. In Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations), pages 393–404, Taiyuan, China. Chinese Information Processing Society of China.