We describe a hidden Markov model (HMM)-based speech synthesis system developed at the Nagoya Institute of Technology (NIT) for Blizzard Challenge 2009. We incorporated several state-of-the-art technologies into this system, including the Speech Transformation and Representation using Adaptive Interpolation of weiGHTed spectrum (STRAIGHT) vocoder, minimum generation error (MGE) training, phone duration modeling, parameter generation algorithm considering global variance, and linear spectrum pair (LSP)-based formant enhancement. The runtime of system synthesizes speech around 0.3xRT (real time ratio), and its footprint is less than 25 MB. The results of listening tests showed that the overall speech quality and intelligibility of our systems are better than most other systems, especially when we have better labeling for a speech corpus.