Abstract / truncated to 115 words (read the full abstract)

Since speaker verification systems (SV) are typically used for access control, the business decision about their deployment is largely dependent on their efficacy and security. This dissertation investigates methods aiming to increase the robustness of SV towards fraud attempts and reverberation mismatch between speaker enrollment and verification. The impact of reverberation is investigated first in the context of speaker verification in a room with randomly distributed microphones. The main contributions of this study include the preferred microphone selection strategy for training and testing of an SV system and a novel feature extraction method, which integrates reverberation robust features with features extracted from a dereverberated signal. The results of the experiments, conducted using all major speaker ... toggle 5 keywords

speaker verification – dereverberation – multichannel linear prediction – replay attack detection – antispoofing

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