Hand Sign Recognition for Sign Language Translation

Communication between sign language users and people who don't know sign language typically depends on either a human interpreter being present or one side learning the other's language, neither of which is always practical in the moment. Existing translation tools that did exist were often too slow or too resource-heavy to use in a real, live conversation, limiting how useful they actually were day to day. There was a clear need for a lightweight, low-latency tool that could help bridge that gap in real time, without requiring specialized hardware.

Sitetisfy built a Python application using MediaPipe's hand-tracking algorithms to detect finger positions and gestures through a standard camera feed in real time. Each detected gesture is classified and mapped to its corresponding letter in the sign language alphabet, with the whole pipeline optimized to keep latency low enough for the output to feel like a live conversation rather than a delayed transcription. Because it runs on MediaPipe rather than specialized recognition hardware, the tool stays accessible and lightweight enough to run on ordinary consumer devices.