Summary of Real-time Multilingual Sign Language Processing, by Amit Moryossef
Real-Time Multilingual Sign Language Processing
by Amit Moryossef
First submitted to arxiv on: 2 Dec 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This research paper presents a novel approach to Sign Language Processing (SLP), an interdisciplinary field combining Natural Language Processing (NLP) and Computer Vision. The paper addresses the limitations of traditional gloss-based systems, which are language-specific and inadequate for capturing the complexity of sign language. By developing more effective technology, researchers aim to improve computational understanding, translation, and production of signed languages. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Sign Language Processing is a special way computers can understand and create sign languages. Right now, most computer programs that try to do this use systems based on written words or phrases. But these systems don’t work very well because they’re not designed for the special ways signs are made. This paper is trying to fix that by finding new ways for computers to understand and create sign languages. |
Keywords
» Artificial intelligence » Natural language processing » Nlp » Translation
