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Abstract Manual annotation for tim-aligning a speech waveform against the corresponding phonetic sequence is a time consuming task.THis research aimed to introduce a completely automated arabic isolated phone speakers independent recognition system. based on wavelet packets best tree encoding feature (WPBTE)is used to find phoneme boundaries along speech utterance. comparison to mel-frequency cepstral coefficients (MFCCS) speech feature in solving the same problem is provided. hidden markov model and gaussian mixture are used for building the statistical models through this research .HTK software toolkit is utilized for implementation of the model. |