Papers by Medet Mukushev

2 papers
Evaluation of Manual and Non-manual Components for Sign Language Recognition (2020.lrec-1)

Copied to clipboard

Challenge: Deaf communities communicate via sign languages to express meaning and intent.
Approach: They used sign samples from 20 commonly used signs in Kazakh-Russian Sign Language (K-RSL) to investigate whether non-manual components would improve sign’s recognition accuracy.
Outcome: The results showed that using non-manual components would improve sign recognition accuracy.
Crowdsourcing Kazakh-Russian Sign Language: FluentSigners-50 (2022.lrec-1)

Copied to clipboard

Challenge: Using crowdsourcing, we created a signer independent dataset for sign language processing.
Approach: They propose to crowdsource a signer independent Kazakh-Russian Sign Language (KRSL) dataset.
Outcome: The proposed dataset consists of 173 sentences performed by 50 signers for 43,250 video samples.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations