­ This paper presents our study on context­independent tone recognition of Vietnamese continuous speech. Each of the six Vietnamese tones is represented by a hidden Markov model (HMM for short) and we used VNSPEECHCORPUS to learn these models in terms of fundamental frequency, F 0 , and short­ time energy. We focus on evaluating the influence of different factors on the tone recognition. The experimental results show that the best method to learn F 0 and energy is to use a logarithmic transformation function and then normalization with mean and mean deviation. In addition, we show that using 8 forms of tones and the discrimination between male and female speakers increase the accuracy of the Vietnamese tone recognition system.