15 accepted papers
Adversarial attacks can mislead automatic speech recognition (ASR) systems into predicting an arbitrary target text, thus posing a clear security threat. To prevent such attacks, we propose DistriBlock, an efficient detection strategy applicable to any ASR system that predicts a probability distribu…
We are proposing a novel framework for author diarization, i.e. attributing comments in online discussions to individual authors. We consider an innovative approach that merges pre-trained neural representations of writing style with author-conditional encoder-decoder diarization, enhanced by a Cond…
Estimating the positions of multiple speakers can be helpful for tasks like automatic speech recognition or speaker diarization. Both applications benefit from a known speaker position when, for instance, applying beamforming or assigning unique speaker identities. Recently, several approaches utili…
End-to-end acoustic speech recognition has quickly gained widespread popularity and shows promising results in many studies. Specifically the joint transformer/CTC model pro-vides very good performance in many tasks. However, under noisy and distorted conditions, the performance still degrades notab…
Audiovisual speaker tracking is an application that has been tackled by a wide range of classical approaches based on Gaussian filters, most notably the well-known Kalman filter. Recently, a specific Kalman filter implementation was proposed for this task, which incorporated dynamic stream weights t…
Deep neural networks can generate images that are astonishingly realistic, so much so that it is often hard for humans to distinguish them from actual photos. These achievements have been largely made possible by Generative Adversarial Networks (GANs). While deep fake images have been thoroughly inv…
Traditional computational authorship attribution describes a classification task in a closed-set scenario. Given a finite set of candidate authors and corresponding labeled texts, the objective is to determine which of the authors has written another set of anonymous or disputed texts. In this work,…
Multimodal data fusion is an important aspect of many object localization and tracking frameworks that rely on sensory observations from different sources. A prominent example is audiovisual speaker localization, where the incorporation of visual information has shown to benefit overall performance,…
Authorship verification tries to answer the question if two documents with unknown authors were written by the same author or not. A range of successful technical approaches has been proposed for this task, many of which are based on traditional linguistic features such as n-grams. These algorithms…
This paper presents a novel framework for active exploration in the context of acoustic simultaneous localization and mapping (SLAM) using a microphone array mounted on a mobile robotic agent. Acoustic SLAM aims at building a map of acoustic sources present in the environment and simultaneously esti…
Audio-visual speech recognition is a promising approach to tackling the problem of reduced recognition rates under adverse acoustic conditions. However, finding an optimal mechanism for combining multi-modal information remains a challenging task. Various methods are applicable for integrating acous…
This study introduces a machine hearing system for robot audition, which enables a robotic agent to pro-actively minimize the uncertainty of sound source location estimates through motion. The proposed system is based on an active exploration approach, providing a means to model and predict effects…
Speaker localization using microphone arrays is typically based on the expected phase and amplitude differences between microphones as a function of the wave arrival direction. However, in rooms with significant reverberation, the direct sound is contaminated by reflections and localization often fa…
Automatic speech recognition (ASR) has become a widespread and convenient mode of human-machine interaction, but it is still not sufficiently reliable when used under highly noisy or reverberant conditions. One option for achieving far greater robustness is to include another modality that is unaffe…
Most of the objective measures employed for speech intelligibility prediction require a clean reference signal, which is not accessible in all realistic scenarios. In this paper, we propose to re-synthesize the relevant features of the clean signal using only the noisy speech signal and utilize them…