Learn More
An increasing number of independent studies have confirmed the vulnerability of automatic speaker verification (ASV) technology to spoofing. However, in comparison to that involving other biometric modalities, spoofing and countermeasure research for ASV is still in its infancy. A current barrier to progress is the lack of standards which impedes the(More)
The molecular and physical information coded within the extracellular milieu is informing the development of a new generation of biomaterials for tissue engineering. Several powerful extracellular influences have already found their way into cell-instructive scaffolds, while others remain largely unexplored. Yet for commercial success tissue engineering(More)
The vulnerability of automatic speaker verification systems to spoofing is now well accepted. While recent work has shown the potential to develop countermeasures capable of detecting spoofed speech signals, existing solutions typically function well only for specific attacks on which they are optimised. Since the exact nature of spoofing attacks can never(More)
This paper presents the ALIZE/SpkDet open source software packages for text independent speaker recognition. This software is based on the well-known UBM/GMM approach. It includes also the latest speaker recognition developments such as Latent Factor Analysis (LFA) and unsupervised adaptation. Discriminant classifiers such as SVM supervectors are also(More)
There are two approaches to speaker diarization. They are bottom-up and top-down. Our work on top-down systems show that they can deliver competitive results compared to bottom-up systems and that they are extremely computationally efficient, but also that they are particularly prone to poor model initialisation and cluster impurities. In this paper we(More)
Embryonic stem cells (ESC) are both a potential source of cells for tissue replacement therapies and an accessible tool to model early embryonic development. Chemical factors such as soluble growth factors and insoluble components of the extracellular matrix are known to affect the differentiation of murine ESCs. However, there is also evidence to suggest(More)
Speaker diarization is the task of determining “who spoke when?” in an audio or video recording that contains an unknown amount of speech and also an unknown number of speakers. Initially, it was proposed as a research topic related to automatic speech recognition, where speaker diarization serves as an upstream processing step. Over recent(More)
While biometric authentication has advanced significantly in recent years, evidence shows the technology can be susceptible to malicious spoofing attacks. The research community has responded with dedicated countermeasures which aim to detect and deflect such attacks. Even if the literature shows that they can be effective, the problem is far from being(More)
This paper presents a new countermeasure for the protection of automatic speaker verification systems from spoofed, converted voice signals. The new countermeasure is based on the analysis of a sequence of acoustic feature vectors using Local Binary Patterns (LBPs). Compared to existing approaches the new countermeasure is less reliant on prior knowledge(More)