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Leveraging Frequency Analysis for Deep Fake Image Recognition
TLDR
It is demonstrated how the frequency representation can be used to identify deep fake images in an automated way, surpassing state-of-the-art methods.
Adversarial Attacks Against Automatic Speech Recognition Systems via Psychoacoustic Hiding
TLDR
A new type of adversarial examples based on psychoacoustic hiding is introduced, which allows us to embed an arbitrary audio input with a malicious voice command that is then transcribed by the ASR system, with the audio signal remaining barely distinguishable from the original signal.
Noise-Adaptive LDA: A New Approach for Speech Recognition Under Observation Uncertainty
TLDR
This work introduces a new strategy: Reducing the speech feature dimensionality for optimal discriminance under observation uncertainty can yield significantly improved recognition performance, and is derived easily via Fisher's criterion of discriminant analysis.
Explainable Authorship Verification in Social Media via Attention-based Similarity Learning
TLDR
This work proposes a substantial extension of a recently published hierarchical Siamese neural network approach, with which it is feasible to learn neural features and to visualize the decision-making process and shows that the proposed method is indeed able to latch on to some traditional linguistic categories.
Imperio: Robust Over-the-Air Adversarial Examples for Automatic Speech Recognition Systems
TLDR
This paper demonstrates the first algorithm that produces generic adversarial examples against hybrid ASR systems, which remain robust in an over-the-air attack that is not adapted to the specific environment and employs the ASR system Kaldi to demonstrate the attack.
Learning Dynamic Stream Weights For Coupled-HMM-Based Audio-Visual Speech Recognition
TLDR
This paper presents a complete framework that allows blind estimation of dynamic stream weights for audio-visual speech recognition based on coupled hidden Markov models (CHMMs) and defines 31-dimensional feature vectors that combine model-based and signal-based reliability measures as inputs to the stream weight estimator.
Robust Speech Recognition of Uncertain or Missing Data - Theory and Applications
TLDR
This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robusts, simultaneous recognition of multiple speech signals, and audiovisual speech recognition.
Dynamic Stream Weighting for Turbo-Decoding-Based Audiovisual ASR
TLDR
This work introduces a strategy for estimating optimal weights for the audio and video streams in turbo-decodingbased ASR using a discriminative cost function and shows that turbo decoding with this maximally discrim inative dynamic weighting of information yields higher recognition accuracy than turbo- decoding-based recognition with fixed stream weights or optimally dynamically weighted audiovisual decoding using coupled hidden Markov models.
SkypeLine: Robust Hidden Data Transmission for VoIP
TLDR
This paper presents SkypeLine, a censorship circumvention system that leverages Direct-Sequence Spread Spectrum (DSSS) based steganography to hide information in Voice-over-IP (VoIP) communication and demonstrates the real-world applicability of the presented system with an exemplary prototype for Skype.
Unacceptable, where is my privacy? Exploring Accidental Triggers of Smart Speakers
TLDR
This paper automates the process of finding accidental triggers and measures their prevalence across 11 smart speakers from 8 different manufacturers using everyday media such as TV shows, news, and other kinds of audio datasets.
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