# Main goals:
- To create a sign language search engine that enables users to easily find sign language content.(MVP - Minimal Viable Product)
- To create an interactive sign language tutoring system that effectively teaches users sign language.(Medium Viable Product)
- To create a machine translation system that accurately and efficiently translates between sign languages and spoken or written language, making communication more accessible for users.(Maximal Viable Product)
### Terms & Definitions
- Minimal Viable Product - The minimum set of features necessary to test the basic functionality of the sign language interface.
- Medium Viable Product - An expanded version of the MVP with additional features to improve usability and functionality.
- Maximal Viable Product - The final version of the product, with all the features and capabilities required for full functionality.


# The tasks can include

- Develop sign language generation and recognition system

- Develop a tool for collecting and labeling sign language data, and create a dataset using this tool

- Use the tool to mark up sign language data, such as videos or images, with linguistic and grammatical information, such as signs, movements, handshape, hand orientation, location, and facial expression

- Develop a sign language search engine that allows users to search for sign language content.

- Develop an interactive sign language tutoring system

- Continuously monitor and analyse the performance of the system to identify areas for improvement.

- Design a UI/UX interface that is easy to navigate and understand for sign language users.

### App task examples:

Data labeling
- Sign language data labeler uses the tool [youtube](https://youtu.be/NIa3q5zdT-U)
- Collection of sign language sentence at NGTU NETI [youtube](https://youtu.be/oLZsv8j_nJ4)

Sign language recognition
- Recognition of Russian fingerspelling [youtube](https://youtu.be/NxdVHfo_ZLo)
- Recognize hand configurations-orientations to present examples of words [youtube](https://youtu.be/VRlgWQFEUzA)
- Static one-handed gestures to present examples of words [youtube](https://youtu.be/qQwLTXNp9DY)
- In the context of the course 'Designing a Machine Learning System', a Telegram bot is demonstrated that is able to recognize the shape of the hand and then match it to the corresponding word in Russian Sign Language. [youtube](https://www.youtube.com/live/3pJSXQuBd-s?feature=share) (see 4:42:37-5:03:16)

UI/UX layout
- Random gesture selection [youtube](https://youtu.be/oOWatIspYwE)
- Search for gesture by word [youtube](https://youtu.be/V1XYH2L7Gfo)
- Sequential display of selected gesture parameters for gesture search [youtube](https://youtu.be/lryv_njvHtE)
- Search for gesture by photo with its performance [youtube](https://youtu.be/jcAkCfhPKls)
- AdaptisCon#2 in Novosibirsk - Presentation of the Russian sign language dictionary [youtube](https://www.youtube.com/live/oKyXMrA6ghs?feature=share) (see 1:48:10-2:22:14 of our speaker)

### Site, bot & mobile apps
- https://signlanguages.ru/
- https://t.me/slsru_bot (In developing)
- iOS app "Signlanguage" [AppStore](https://apps.apple.com/ru/app/signlanguages/id1602656863)
-  Android app "Signlanguage" [PlayMarket](https://play.google.com/store/apps/details?id=com.nstu.rsl)

# Social media:
- [github](https://github.com/orgs/sign-language-interface)
- [vk](https://vk.com/signlanguages)
- [telegram](https://t.me/slsru)
- [instagram](https://www.instagram.com/signlanguages.ru)

# About
Email: alexeyayaya@gmail.com - Alexey Prikhodko

- Alexey Prikhodko - Domain expert, ML developer
- Julia Prikhodko - Sign language data labeler and informer
- Mark Belousov - Frontend-developer, system analyst

Sign Language Interface project aims to improve accessibility of technology for individuals who use sign languages by incorporating sign language recognition, generation, translation, and tutoring functionality into UI/UX design and AI systems.

Sign language interfaceactive, Founded 4 years ago

Sign language interface
active,
Founded 4 years ago