22. An apparatus for creating context dependent synthesis phoneme-based units of a text-to-speech system, the method comprising the steps of: means for storing input speech from a target speaker and corresponding phonetic symbols of the input speech; a training module for identifying each unique context-dependent phoneme-based unit of the input speech and training a Hidden Markov Model (HMM) for each unique context-dependent phoneme-based unit based on context of at least one immediately preceding and succeeding phoneme-based unit, wherein a central phoneme-based unit is selected from a group consisting of a phoneme and a diphone; a clustering module for clustering the HMMs into groups having the same central phoneme-based unit that sound similar but have different preceding or succeeding phoneme-based units and selecting one of context-dependent phoneme-based unit of each group to represent the corresponding group.
22. An apparatus for creating context dependent synthesis phoneme-based units of a text-to-speech system, the method comprising the steps of: means for storing input speech from a target speaker and corresponding phonetic symbols of the input speech; a training module for identifying each unique context-dependent phoneme-based unit of the input speech and training a Hidden Markov Model (HMM) for each unique context-dependent phoneme-based unit based on context of at least one immediately preceding and succeeding phoneme-based unit, wherein a central phoneme-based unit is selected from a group consisting of a phoneme and a diphone; a clustering module for clustering the HMMs into groups having the same central phoneme-based unit that sound similar but have different preceding or succeeding phoneme-based units and selecting one of context-dependent phoneme-based unit of each group to represent the corresponding group. 23. The apparatus of claim 22 wherein the clustering module selects at least two context-dependent phoneme-based units to represent at least one of the groups.