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Auflistung nach Autor:in "Evans, Nicholas"

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  • Konferenzbeitrag
    Enhanced low-latency speaker spotting using selective cluster enrichment
    (BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group, 2018) Patino, Jose; Delgado, Héctor; Evans, Nicholas
    Low-latency speaker spotting (LLSS) calls for the rapid detection of known speakers within multi-speaker audio streams. While previous work showed the potential to develop efficient LLSS solutions by combining speaker diarization and speaker detection within an online processing framework, it failed to move significantly beyond the traditional definition of diarization. This paper shows that the latter needs rethinking and that a diarization sub-system tailored to the end application, rather than to the minimisation of the diarization error rate, can improve LLSS performance. The proposed selective cluster enrichment algorithm is used to guide the diarization system to better model segments within a multi-speaker audio stream and hence detect more reliably a given target speaker. The LLSS solution reported in this paper shows that target speakers can be detected with a 16% equal error rate after having been active in multi-speaker audio streams for only 15 seconds.
  • Konferenzbeitrag
    Re-assessing the threat of replay spoofing attacks against automatic speaker verification
    (BIOSIG 2014, 2014) Alegre, Federico; Janicki, Artur; Evans, Nicholas
    This paper re-examines the threat of spoofing or presentation attacks in the context of automatic speaker verification (ASV). While voice conversion and speech synthesis attacks present a serious threat, and have accordingly received a great deal of attention in the recent literature, they can only be implemented with a high level of technical know-how. In contrast, the implementation of replay attacks require no specific expertise nor any sophisticated equipment and thus they arguably present a greater risk. The comparative threat of each attack is re-examined in this paper against six different ASV systems including a state-of-the-art iVector-PLDA system. Despite the lack of attention in the literature, experiments show that low-effort replay attacks provoke higher levels of false acceptance than comparatively higher-effort spoofing attacks such as voice conversion and speech synthesis. Results therefore show the need to refocus research effort and to develop countermeasures against replay attacks in future work.