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State-of-the-Art Performance in Text-Independent Speaker Verification Through Open-Source Software

Abstract : —This paper illustrates an evolution in state-of-the-art speaker verification by highlighting the contribution from newly developed techniques. Starting from a baseline system based on Gaussian mixture models that reached state-of-the-art performances during the NIST'04 SRE, final systems with new intersession compensation techniques show a relative gain of around 50%. This work highlights that a key element in recent improvements is still the classical maximum a posteriori (MAP) adaptation, while the latest compensation methods have a crucial impact on overall performances. Nuisance attribute projection (NAP) and factor analysis (FA) are examined and shown to provide significant improvements. For FA, a new symmetrical scoring (SFA) approach is proposed. We also show further improvement with an original combination between a support vector machine and SFA. This work is undertaken through the open-source ALIZE toolkit.
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Driss Matrouf, Nicolas Scheffer, Jean-François Bonastre. State-of-the-Art Performance in Text-Independent Speaker Verification Through Open-Source Software. IEEE Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2007, ⟨10.1109/TASL.2007.902877⟩. ⟨hal-01311358⟩



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