Social Signal Processing for Android SSJ is an extensible android framework for social signal processing in an ouț of lab envirnoment. It packages common signal processing tools in a flexible, mobile friendly Java library which can be easily integrated into Android Apps. Features Realtime signal processing using independent components as processing steps in a pipeline Synchronized data streams Support for most standard Android sensors (camera, microphone, IMU, GPS, ...) Support for external sensors via Bluetooth (e.g. Myo, Empatica, MS Band 2, Angel Sensor, ...) Advanced signal processing functionality, including machine learning approaches (Neural Networks, SVM, NaiveBayes) On device model training capabilities (batch and online learning) I/O functionality: local storage, WiFi, Bluetooth Live data visualization (using GraphView library) SSJ Creator: Android App for building, editing and running SSJ pipelines without writing a single line of code About The Social Signal Processing for Java/Android (SSJ) framework is being developed at the Lab for Human Centered Multimedia of the University of Augsburg. The authors of the framework are: Ionut Damian, Michael Dietz, Frank Gaibler, Daniel Langerenken, Simon Flutura, Vitalijs Krumins, Antonio Grieco. SSJ has been inspired by the SSI (http://openssi.net) framework. SSJ is not a one-to-one port of SSI to Java, it is an approximation. Nevertheless, it borrows a lot of programming patterns from SSI and preserves the same vision for signal processing which makes SSI great. It then packages everything in a flexible, mobile friendly Java library which can be easily integrated into Android Apps.