This thesis discusses the accent modeling of multi-speaker Mandarin speech based on the existing speaker-dependnet hierarchical prosodic model (SR-HPM). It first constructs a compact multi-speaker SR-HPM using a speech corpus produced by 204 speakers with different accents. It then adopts the adaptative training technique to construct four accent-dependent SR-HPMs with the multi-speaker SR-HPM as the reference model. Through analyzing these four models, many distinct prosody pronunciation features for each accent of Mandarin speech can be found. These observations conform to our prior linguistic knowledge. An application of using these accent-dependnet SR-HPMs to construct personalized TTS systems with their own accent is realized. Both objective and subjective tests confirmed the high performances of these TTS systems