15 accepted papers
The vast majority of approaches to speaker anonymization involve the extraction of fundamental frequency estimates, linguistic features and a speaker embedding which is perturbed to obfuscate the speaker identity before an anonymized speech waveform is resynthesized using a vocoder. Recent work has…
A reliable deepfake detector or spoofing countermeasure (CM) should be robust in the face of unpredictable spoofing attacks. To encourage the learning of more generaliseable artefacts, rather than those specific only to known attacks, CMs are usually exposed to a broad variety of different attacks d…
The success of deep learning in speaker recognition relies heavily on the use of large datasets. However, the data-hungry nature of deep learning methods has already being questioned on account the ethical, privacy, and legal concerns that arise when using large-scale datasets of natural speech coll…
Spoofing countermeasure (CM) and automatic speaker verification (ASV) sub-systems can be used in tandem with a backend classifier as a solution to the spoofing aware speaker verification (SASV) task. The two sub-systems are typically trained independently to solve different tasks. While our previous…
StressID is a new dataset specifically designed for stress identification from unimodal and multimodal data. It contains videos of facial expressions, audio recordings, and physiological signals. The video and audio recordings are acquired using an RGB camera with an integrated microphone. The physi…
Substantial progress in spoofing and deepfake detection has been made in recent years. Nonetheless, the community has yet to make notable inroads in providing an explanation for how a classifier produces its output. The dominance of black box spoofing detection solutions is at further odds with the…
The current outbreak of a coronavirus, has quickly escalated to become a serious global problem that has now been declared a Public Health Emergency of International Concern by the World Health Organization. Infectious diseases know no borders, so when it comes to controlling outbreaks, timing is ab…
This paper introduces RawBoost, a data boosting and augmentation method for the design of more reliable spoofing detection solutions which operate directly upon raw waveform inputs. While RawBoost requires no additional data sources, e.g. noise recordings or impulse responses and is data, applicatio…
Spoofing countermeasures aim to protect automatic speaker verification systems from being manipulated by spoofed speech signals. While results from the most recent ASVspoof 2019 evaluation show great potential to detect most forms of attack, some continue to evade detection. This paper reports the f…
Artificial bandwidth extension (ABE) algorithms have been developed to estimate missing highband frequency components (4-8kHz) to improve quality of narrowband (0-4kHz) telephone calls. Most ABE solutions employ deep neural networks (DNNs) due to their well-known ability to model highly complex, non…
Artificial bandwidth extension (ABE) algorithms can improve speech quality when wideband devices are used with narrowband devices or infrastructure. Most ABE solutions employ some form of memory, implying high-dimensional feature representations that increase both latency and complexity. Dimensional…
Many smart devices now support high-quality speech communication services at super-wide bandwidths. Often, however, speech quality is degraded when they are used with networks or devices which lack super-wideband support. Artificial bandwidth extension can then be used to improve speech quality. Whi…
Artificial bandwidth extension (ABE) algorithms have been developed to improve speech quality when wideband devices are used in conjunction with narrowband devices or infrastructure. While past work points to the benefit of using contextual information or memory for ABE, an understanding of the rela…
Most artificial bandwidth extension (ABE) algorithms are based on the classical source-filter model of speech production. This approach generally requires the dual extension of each component through independent processing. Alternative approaches reported recently operate on the spectrum. With human…
This paper describes a new database for the assessment of automatic speaker verification (ASV) vulnerabilities to spoofing attacks. In contrast to other recent data collection efforts, the new database has been designed to support the development of replay spoofing countermeasures tailored towards t…