This paper presents speech processing and recognition system for Myanmar continuous language. The speech segmentation methods are based on two simple speech features, namely time domain features and frequency features. To detect the word boundaries, dynamic thresholding method is applied. Then, important features of speech features are extracted by LPC (linear predictive coding) and GTCC (gamma tone cepstral coefficient) approach. K-means is used in feature clustering and HMM is used in recognition process. All the algorithms used in this work are implemented in Matlab. The system obtained the average word error rate of 4.16 and 0.479 with LPC and GTCC feature extraction techniques respectively.