22. The computer readable medium of claim 19 , further comprising an act of segmenting the voice signal into a plurality of frames, each of the plurality of frames corresponding to a respective interval of the voice signal, and wherein the acts of: detecting a plurality of candidate features includes an act of detecting a plurality of candidate features in each of the plurality of frames; and grouping the plurality of candidate features includes an act of grouping different combinations of the plurality of candidate features detected in each of the plurality of frames into a respective plurality of candidate feature sets, each of the plurality of candidate feature sets associated with one of the plurality of frames from which the corresponding plurality of candidates features was detected, and further grouping different combinations of the plurality of candidate feature sets to form a respective plurality of candidate feature tracts.
22. The computer readable medium of claim 19 , further comprising an act of segmenting the voice signal into a plurality of frames, each of the plurality of frames corresponding to a respective interval of the voice signal, and wherein the acts of: detecting a plurality of candidate features includes an act of detecting a plurality of candidate features in each of the plurality of frames; and grouping the plurality of candidate features includes an act of grouping different combinations of the plurality of candidate features detected in each of the plurality of frames into a respective plurality of candidate feature sets, each of the plurality of candidate feature sets associated with one of the plurality of frames from which the corresponding plurality of candidates features was detected, and further grouping different combinations of the plurality of candidate feature sets to form a respective plurality of candidate feature tracts. 23. The computer readable medium of claim 22 , wherein forming the plurality of voice waveforms includes forming the plurality of voice waveforms, each of the plurality of voice waveforms being formed, at least in part, from a respective one of the plurality of candidate feature tracts, and wherein the act of selecting the at least one of the plurality of candidate feature sets includes an act of selecting one of the plurality of candidate feature tracts associated with a respective one of the plurality of voice waveforms that is most similar to the voice signal according to the first criteria, the selected one of the plurality of feature tracts being used to train, at least in part, the voice synthesis model.