Quasi text-independent speaker-verification based on pattern matching

We present a new approach to quasi text-independent speaker verification based on pattern matching. Our method first seeks phonetically matched segments in two speech signals. For all aligned frame pairs of these segments we compute the probability that they were uttered by the same speaker. Based on these frame-level probabilities we take the decision whether the two signals were spoken by the same speaker or not. Our method to find phonetically matched segments does not depend on a speech recognizer. We show that our system performs better than a baseline speaker verification system based on Gaussian mixture models when the signals are long enough. Especially interesting is the fact that a combination of the devised system with the baseline system performs much better than either of the systems alone.