Speech recognition using the probabilistic neural network

Raymond Low, Roberto Togneri
1998 5th International Conference on Spoken Language Processing (ICSLP 1998)   unpublished
A novel technique for speaker independent automated speech recognition is proposed. We take a segment model approach to Automated Speech Recognition (ASR), considering the trajectory of an utterance in vector space, then classify using a modified Probabilistic Neural Network (PNN) and maximum likelihood rule. The system performs favourably with established techniques. Our system achieves in excess of 94% with isolated digit recognition, 88% with isolated alphabetic letters, and 83% with the
more » ... usable /e/ set. A favourable compromise between recognition accuracy and computer memory and speech can also be reached by performing clustering on the training data for the PNN.
doi:10.21437/icslp.1998-840 fatcat:pyxhfthqyndlvhoxf37snfoo4y