Michael A. Lund

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A robust speaker verification algorithm based on sequential hypothesis testing is presented. In speaker verification, the system performance is severely degraded by deviations from the nominal statistical speaker models caused by insufficient training data, varying microphone and transmission line characteristics, and different levels and types of(More)
BBN’s baseline language identification (LID) system tokenizes utterances based on an English Hidden Markov Model (HMM) phone recognizer and uses language-dependent phone-bigram models to discriminate between languages. This is clearly a suboptimal procedure, as English phone models may fail to provide a meaningful tokenization of non-English speech. In this(More)
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