UR channel-robust synthetic speech detection system for ASVspoof 2021
In this paper, we present UR-AIR system submission to the logical access (LA) and the
speech deepfake (DF) tracks of the ASVspoof 2021 Challenge. The LA and DF tasks focus …
speech deepfake (DF) tracks of the ASVspoof 2021 Challenge. The LA and DF tasks focus …
A study on data augmentation in voice anti-spoofing
In this paper we perform an in depth study of how data augmentation techniques improve
synthetic or spoofed audio detection. Specifically, we propose methods to deal with channel …
synthetic or spoofed audio detection. Specifically, we propose methods to deal with channel …
Domain generalization via aggregation and separation for audio deepfake detection
In this paper, we propose an Aggregation and Separation Domain Generalization (ASDG)
method for Audio DeepFake Detection (ADD). Fake speech generated from different …
method for Audio DeepFake Detection (ADD). Fake speech generated from different …
An empirical study on channel effects for synthetic voice spoofing countermeasure systems
Spoofing countermeasure (CM) systems are critical in speaker verification; they aim to
discern spoofing attacks from bona fide speech trials. In practice, however, acoustic …
discern spoofing attacks from bona fide speech trials. In practice, however, acoustic …
Device-robust acoustic scene classification via impulse response augmentation
The ability to generalize to a wide range of recording devices is a crucial performance factor
for audio classification models. The characteristics of different types of microphones …
for audio classification models. The characteristics of different types of microphones …
Investigations on end-to-end audiovisual fusion
Audiovisual speech recognition (AVSR) is a method to alleviate the adverse effect of noise
in the acoustic signal. Leveraging recent developments in deep neural network-based …
in the acoustic signal. Leveraging recent developments in deep neural network-based …
DENT-DDSP: Data-efficient noisy speech generator using differentiable digital signal processors for explicit distortion modelling and noise-robust speech recognition
The performances of automatic speech recognition (ASR) systems degrade drastically under
noisy conditions. Explicit distortion modelling (EDM), as a feature compensation step, is able …
noisy conditions. Explicit distortion modelling (EDM), as a feature compensation step, is able …
A fused speech enhancement framework for robust speaker verification
Y Wu, T Li, J Zhao, Q Wang, J Xu - IEEE Signal Processing …, 2023 - ieeexplore.ieee.org
Robust speaker verification (RSV) under noisy conditions is still a challenging task.
Recently, some task-specific speech enhancement (SE) approaches are proposed and …
Recently, some task-specific speech enhancement (SE) approaches are proposed and …
Investigations on audiovisual emotion recognition in noisy conditions
In this paper we explore audiovisual emotion recognition under noisy acoustic conditions
with a focus on speech features. We attempt to answer the following research questions:(i) …
with a focus on speech features. We attempt to answer the following research questions:(i) …
Audio codec simulation based data augmentation for telephony speech recognition
Real telephony speech recognition task is challenging due to 1) diversified channel
distortions and 2) limited access to the real data because of the data privacy consideration …
distortions and 2) limited access to the real data because of the data privacy consideration …