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This letter proposes an HMM-based Text-to-Speech (TTS) system using waveform interpolation (WI)-based speech analysis and synthesis. The synthesized speech quality of the proposed system is significantly improved due to adopting an enhanced excitation modeling technique. The decomposition of characteristic waveform (CW) into slowly evolving waveform (SEW) and rapidly evolving waveform (REW) is efficient not only for excitation modeling but also for training process of HMMs. Objective and subjective test results verify the superiority of the proposed approach to conventional ones.