Milk is a machine learning toolkit in Python. Its focus is on supervised classification with several classifiers available: SVMs (based on libsvm), k-NN, random forests, and decision trees. It also performs feature selection. These classifiers can be combined in many ways to form different classification systems. For unsupervised learning, milk supports k-means clustering and affinity propagation.
Property Binder is a Java library that provides typed access to entries in properties files. It offers such access by allowing a programmer to provide it a Java interface whose methods represent the keys of the properties file. The methods can be annotated to indicate what property the method represents, what default value(s) it should assume if the property is not present, and what pattern separates the individual values of multi-valued properties.
The dywapitchtrack library computes the pitch of an audio stream in realtime. The pitch is the main frequency of the waveform (the "note" being played or sung). It is expressed as a float in Hz. dywapitchtrack is based on a custom-tailored algorithm which is of very high quality, very accurate (precision < 0.05 semitones), with very low latency (< 23 ms) and very low error rates. It has been thoroughly tested on the human voice.