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HMM-Based Korean Speech Synthesizer with Two-Band Mixed Excitation Model for Embedded Applications

Speech interface may be the first choice as a user interface for robots or hand-held devices such as personal digital assistants (PDAs) and portable multimedia players (PMPs). However, those devices have the limitation of the memory space and the computation power. The hidden Markov model (HMM)-based speech synthesis is presently considered to be suitable for the embedded systems. This thesis describes an HMM-based Korean speech synthesis, spectral parameter comparison, and the suggested two-band excitation model for the HMM-based speech synthesis. Firstly, development of an HMM-based Korean speech synthesis system and its evaluation is presented. Statistical HMM models for Korean speech units are trained with the hand-labeled speech database includ-