A primary challenge for the deaf and hearing-impaired community stems from
the communication gap with the hearing society, which can greatly impact their
daily lives and result in social exclusion. To foster inclusivity in society,
our endeavor focuses on developing a cost-effective, resource-efficient, and
open technology based on Artificial Intelligence, designed to assist people in
learning and using Sign Language for communication. The analysis presented in
this research paper intends to enrich the recent academic scientific literature
on Sign Language solutions based on Artificial Intelligence, with a particular
focus on American Sign Language (ASL). This research has yielded promising
preliminary results and serves as a basis for further development.

开发一种基于人工智能的成本效益高、资源高效和开放的技术，旨在帮助人们学习和使用手语进行交流，以促进社会的包容性。该研究分析了基于人工智能的手语解决方案，特别聚焦美国手语，取得了令人满意的初步结果，并为进一步发展奠定了基础。

一个实时的人工智能学习手语的系统

A real-time Artificial Intelligence system for learning Sign Language

We propose eXtensible Prompt (X-Prompt) for prompting a large language model
(LLM) beyond natural language (NL). X-Prompt instructs an LLM with not only NL
but also an extensible vocabulary of imaginary words that are introduced to
help represent what NL words hardly describe, allowing a prompt to be more
descriptive. Like NL prompts, X-Prompt is out-of-distribution (OOD) robust, for
which we propose context-guided learning with prompt augmentation to learn its
imaginary words for general usability, enabling them to use in different prompt
contexts for fine-grain specifications. The promising results of X-Prompt
demonstrate its potential of approaching advanced interaction between humans
and LLMs to bridge their communication gap.

提出了一种名为 X-Prompt 的方法，通过引入虚构单词的可扩展词汇表，指导大型语言模型（LLM）完成超越自然语言的任务，使得提示更具描述性，并实现了上下文引导学习及提示增强，从而使其虚构单词可以用于不同的提示上下文，以达到精细的规范。该方法在人类与 LLMs 间构建了通信桥梁，有望实现更高级的交互。