Robust speech parameters extraction for word recognition in noise using neural networks

An attempt was made to enhance the performance of a DTW (dynamic time warping) speech recognizer by preprocessing speech parameters using a neural network transformation. A multilayer perceptron trained with speech utterances of a single speaker has been used in front of a DTW recognizer. Results show an improvement of about 15% in the recognition rate in all cases, even with a speaker that was not used for training. If the network is not completely speaker independent, a dynamic adaptation to the speaker could be performed.<<ETX>>