Summary of Kenyan Sign Language (ksl) Dataset: Using Artificial Intelligence (ai) in Bridging Communication Barrier Among the Deaf Learners, by Lilian Wanzare et al.
Kenyan Sign Language (KSL) Dataset: Using Artificial Intelligence (AI) in Bridging Communication Barrier among the Deaf Learners
by Lilian Wanzare, Joel Okutoyi, Maurine Kang’ahi, Mildred Ayere
First submitted to arxiv on: 23 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The AI4KSL project aims to develop an artificial intelligence-based assistive technology that translates English into Kenyan Sign Language (KSL) to bridge the communication gap between deaf and hearing individuals in Kenya. The two-year research project collects spontaneous and elicited data from a representative sample of the Kenyan deaf community, comprising 14,000 English sentences with corresponding KSL gloss, 20,000 signed KSL videos, and 10,000 segmented KSL videos. The dataset is designed to facilitate inclusion and academic achievement among deaf learners in Kenya. The project’s methodology for building the dataset involves collecting data from 48 teachers and tutors of the deaf and 400 learners who are Deaf through sign language elicitation tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The AI4KSL project helps deaf people in Kenya communicate better with hearing people by creating a digital tool that translates English into Kenyan Sign Language. The researchers collected lots of data from deaf teachers, tutors, and students to make this tool work. They got about 14,000 sentences and over 20,000 videos of sign language. This will help deaf kids learn better and get an education like everyone else. |
