Transition-oriented hidden Markov models for speaker verification

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Method for Adaptive Training of Polynomial Networks with Applications to Speaker Verification

Speaker verification is the process of determining the validity of a claimed identity through voice. Traditional approaches to this problem are Gaussian mixture models and hidden Markov models. Although these methods work well, they are difficult to employ in an adaptive framework because of the iterative nature of training. Ideally, as we acquire new-labeled input, we would like to update the ...

Speaker verification based on phonetic decision making

Speaker verification based on phone modelling is examined in this paper. Phone modelling is attractive, because different phonemes have different levels of usefulness for speaker recognition, and because phone modelling essentially makes a speaker verification algorithm text independent. The speaker verification system used here is based on a two stage approach, where speech recognition (segmen...

On Word Boundary Detection in Digit-based Speaker Verification

In an automatic speaker verification (ASV) system with prompted passwords, we use vocabulary-dependent hidden Markov models and rely on the ability to explicitly locate the corresponding words and their boundaries in the speech signal. In an experiment on 41 speakers in a Swedish telephone speech database, we compare the use of utterance segmentation produced by automatic and manual methods, an...