208 citations · 323 across the 28 of their papers we have counts for
8 papers · 1 filter
DistriBlock: Identifying adversarial audio samples by leveraging characteristics of the output distribution
Matías Pizarro, Dorothea Kolossa, Asja Fischer
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, w…
PILOT: Introducing Transformers for Probabilistic Sound Event Localization
Christopher Schymura, Benedikt Bönninghoff, Tsubasa Ochiai +5
Sound event localization aims at estimating the positions of sound sources in the environment with respect to an acoustic receiver (e.g. a microphone array). Recent advances in thi…
Unsupervised Classification of Voiced Speech and Pitch Tracking Using Forward-Backward Kalman Filtering
Benedikt Boenninghoff, Robert M. Nickel, Steffen Zeiler +1
The detection of voiced speech, the estimation of the fundamental frequency, and the tracking of pitch values over time are crucial subtasks for a variety of speech processing tech…
Exploiting Attention-based Sequence-to-Sequence Architectures for Sound Event Localization
Christopher Schymura, Tsubasa Ochiai, Marc Delcroix +4
Sound event localization frameworks based on deep neural networks have shown increased robustness with respect to reverberation and noise in comparison to classical parametric appr…
Data Fusion for Audiovisual Speaker Localization: Extending Dynamic Stream Weights to the Spatial Domain
Julio Wissing, Benedikt Boenninghoff, Dorothea Kolossa +6
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 posi…
VenoMave: Targeted Poisoning Against Speech Recognition
Hojjat Aghakhani, Lea Schönherr, Thorsten Eisenhofer +4
Despite remarkable improvements, automatic speech recognition is susceptible to adversarial perturbations. Compared to standard machine learning architectures, these attacks are si…