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The goal of this project is to investigate optimal ways to do genre classification for the ten indigenous South African languages. Funded by Dept of Arts and Culture of the SA Government.
http://www.trifonius.co.za/projects/genre-classification
Research tool for interactive training of artificial neural networks.
BNNS is a research tool for interactive training of artificial neural networks based on the Response Function Plots visualization method. It enables users to simulate, visualize and interact in the learning process of a Multi-Layer Perceptron on tasks which have a 2D character. Tasks like the famous two-spirals task or classification of satellite image data.
Featurama is a library that implements various sequence-labeling algorithms. Currently Michael Collins' averaged perceptron algorithm is fully implemented.
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BCAR is a library for the associative classification, which denotes "Boosting
Class Association Rules". BCAR provides a general tool for classification tasks
with various types of input data.
openEAR is the Munich Open-Source Emotion and Affect Recognition Toolkit developed at the Technische Universität München (TUM). It provides efficient (audio) feature extraction algorithms implemented in C++, classfiers, and pre-trained models on well-known emotion databases. It is now maintained and supported by audEERING. Updates will follow soon.