ESCA Workshop on Automatic Speaker Recognition, Identification, and Verification

Martigny, Switzerland
April 7-9, 1994

Text-Independent Speaker Verification Using Neural Networks

Hiroaki Hattori

Information Technology Research Laboratories, NEC, Japan

This paper presents a new prediction error normalisation method for speaker verification using predictive neural networks. A prediction error obtained by a predictive neural network strongly depends on a particular input and the goodness of the fit is difficult to determine by comparing the value with a fixed threshold. We propose a prediction error normalisation algorithm which uses the prediction error obtained by a network trained for multiple categories as a measurement of predictability of an input.

The algorithm was evaluated in text-independent speaker verification. Without normalisation, an equal error rate of 41.2% was achieved for 12 male speaker verification, using the normalisation, the equal error rate was improved drastically to 1.5%. This result proved the effectiveness of the proposed algorithm.

The proposed algorithm is also applicable to other speech processing areas which involve comparison with a threshold such as word spotting and rejection of unknown words.

Full Paper

Bibliographic reference.  Hattori, Hiroaki (1994): "Text-independent speaker verification using neural networks", In ASRIV-1994, 103-106.