tone tempo viverance

The aspects of my research that set it apart from other speech recognizing software is that they attempt to match phonemes with phonetic words. My approach builds on this but uses a blackboard approach. A  blackboard has multiple agents that evaluate an aspect and throws throws it into a processing system. In this approach the words are a feature and so are tone (pitch) tempo and viverance. This is important because like my paper Jurassic Park Extrapolation Renders Speech to Speech engine greater accuracy mentions the brain is constantly bombarded with signals and information. The brain has trained itself to ignore some sounds such as the 60 hertz drone of a light bulb fixture. The brain needs some difference and variance in order to stay focused. When a robotic voice speaks it is often draining to listen to. I hope to find a feature set to annotate and make computers easier to listen to. I am currently working on looking at integrating the Neuromorphic Vision C++ Toolkit with gbbopen and pybrain. I hope to be able to understand the algorithms well enough to port them all to python and so it can run on an android. GBBOpen is written in lisp and neuromorphic Vision C++ Toolkit is written in C++.