document: Speaker identification from voice using neural networks The paper provides three different schemes for speaker identification of personnel from their voice using artificial neural networks . The first scheme recognizes speakers by employing the classical backpropagation algorithm pre-trained with known voice samples of the persons . The second scheme provides a framework for classifying the known training samples of the voice features using a hierarchical architecture realized with a self-organizing feature map neural net . The first scheme is highly robust as it is capable of identifying the personnel from their noisy voice samples , but because of its excessive training time it has limited applications for a large voice database . The second scheme though not so robust as the former , however , can classify an unknown voice sample to its nearest class . The time needed for classification by the first scheme is always unique irrespective of the voice sample . It is proportional to the number of feedforward layers in the network . The time-requirement of the second classification scheme , however , is not free from the voice features and is proportional to the number of 2D arrays traversed by the algorithm on the hierarchical structure . The third scheme is highly robust and mis-classification is as low as 0.2 per cent . The third scheme combines the composite benefits of a radial basis function neural net and backpropagation trained neural net
doc_bio_tags: B I O O O O O O O O O O O O B I O B O O O O B I I O O O O O O O O O O B I O O B I I O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O B O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I I O O O O O
extractive_keyphrases: speaker identification artificial neural networks personnel hierarchical architecture backpropagation algorithm classification feedforward layers 2d arrays radial basis function neural net known voice samples
abstractive_keyphrases: self-organizing feature map pre-training