The Social Signal Interpretation (SSI) framework offers tools to record, analyse and recognize human behavior in real-time, such as gestures, mimics, head nods, and emotional speech. Following a patch-based design pipelines are set up from autonomic components and allow the parallel and synchronized processing of sensor data from multiple input devices. In particularly SSI supports the machine learning pipeline in its full length and offers a graphical interface that assists a user to collect own training corpora and obtain personalized models. In addition to a large set of built-in components SSI also encourages developers to extend available tools with new functions. For inexperienced users an easy-to-use XML editor is available to draft and run pipelines without special programming skills. SSI is written in C++ and optimized to run on computer systems with multiple CPUs. Binaries and source code are freely available under GPL.
For more information visit: http://openssi.net