A realistic speech synthesis tool could be used in dynamic therapeutic applications as well as revolutionize the animation pipeline in the entertainment industry. In this thesis, we propose a data-driven speech synthesis method that uses Viseme Transition Units (3D animation data describing the transition between mouth shapes) in the stead of the static visemes used in classic data-driven speech synthesis methods. To test this method, viseme transitions were recorded using optical flow and blob tracking algorithms, analyzed, and imported into Autodesk Maya to dynamically animate a custom mouth rig based on user input.