Language-independent voice passphrase verification

Voice passphrase verification is the task of deciding whether an audio recording contains a given passphrase. It is usually done by evaluating the likelihood of the passphrase reference text given the audio, which requires a different ASR system for each language. Here we look at verification when the passphrase reference is an audio recording instead of a text. We propose a decision likelihood ratio derived from a generative model. Training is unsupervised and needs only audio, without labelling, so the method applies to any language for which recorded audio exists. We report experiments on English and Urdu telephone speech, and show that our model-based likelihood ratio largely outperforms a baseline of DTW based on MFCC feature vectors.