Slovo: Russian Sign Language Dataset
This provides a new dataset for Russian Sign Language recognition, addressing a gap for hard-of-hearing communities in Russia, but it is incremental as it applies existing methods to a new language-specific dataset.
The paper tackles the challenge of sign language recognition by creating Slovo, a Russian Sign Language dataset with 20,000 FullHD recordings across 1,000 isolated gestures from 194 signers, and demonstrates its utility by training and evaluating neural networks on it.
One of the main challenges of the sign language recognition task is the difficulty of collecting a suitable dataset due to the gap between hard-of-hearing and hearing societies. In addition, the sign language in each country differs significantly, which obliges the creation of new data for each of them. This paper presents the Russian Sign Language (RSL) video dataset Slovo, produced using crowdsourcing platforms. The dataset contains 20,000 FullHD recordings, divided into 1,000 classes of isolated RSL gestures received by 194 signers. We also provide the entire dataset creation pipeline, from data collection to video annotation, with the following demo application. Several neural networks are trained and evaluated on the Slovo to demonstrate its teaching ability. Proposed data and pre-trained models are publicly available.