A method and system are provided for speech recognition. The speech recognition method includes the steps of preparing training data representing acoustic parameters of each of phonemes at each time frame; receiving an input signal representing a sound to be recognized and converting the input signal to input data; comparing the input data at each frame with the training data of each of the phonemes to derive a similarity measure of the input data with respect to each of the phonemes; and processing the similarity measures obtained in the comparing step using a neural net model governing development of activities of plural cells to conduct speech recognition of the input signal. In the processing step, each cell is associated with one respective phoneme and one frame, a development of the activity of each cell at each frame in the neural net model is suppressed by the activities of other cells on the same frame corresponding to different phonemes, and the development of the activity of each cell at each frame being enhanced by the activities of other cells corresponding to the same phoneme at different frames. In the process, the phoneme of a cell that has developed the highest activity is determined as a winner at the corresponding frame to produce a list of winners at respective frames. A phoneme is outputted as a recognition result for the input signal in accordance with the list of the winners at the respective frames that have been determined in the step of processing.
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