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Learning to Fool the Speaker Recognition
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1006/dspr.1999.0361openalex-snapshot
Speaker Verification Using Adapted Gaussian Mixture Models
inferredcites →https://doi.org/10.1007/s11633-019-1211-xopenalex-snapshot
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
inferredcites →https://doi.org/10.1109/access.2018.2807385openalex-snapshot
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
inferredcites →https://doi.org/10.1109/btas.2016.7791200openalex-snapshot
Overview of BTAS 2016 speaker anti-spoofing competition
inferredcites →https://doi.org/10.1109/cvpr.2017.17openalex-snapshot
Universal Adversarial Perturbations
inferredcites →https://doi.org/10.1109/eurosp.2016.36openalex-snapshot
The Limitations of Deep Learning in Adversarial Settings
inferredcites →https://doi.org/10.1109/icassp.2001.941023openalex-snapshot
Perceptual evaluation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs
inferredcites →https://doi.org/10.1109/icassp.2015.7178964openalex-snapshot
Librispeech: An ASR corpus based on public domain audio books
inferredcites →https://doi.org/10.1109/icassp.2018.8461375openalex-snapshot
X-Vectors: Robust DNN Embeddings for Speaker Recognition
inferredcites →https://doi.org/10.1109/icassp.2018.8462165openalex-snapshot
Towards Directly Modeling Raw Speech Signal for Speaker Verification Using CNNS
inferredcites →https://doi.org/10.1109/icassp.2018.8462575openalex-snapshot
A Complete End-to-End Speaker Verification System Using Deep Neural Networks: From Raw Signals to Verification Result
inferredcites →https://doi.org/10.1109/icassp.2018.8462693openalex-snapshot
Fooling End-To-End Speaker Verification With Adversarial Examples
inferredcites →https://doi.org/10.1109/icassp.2019.8683713openalex-snapshot
The Pytorch-kaldi Speech Recognition Toolkit
inferredcites →https://doi.org/10.1109/icassp40776.2020.9053058openalex-snapshot
Learning to Fool the Speaker Recognition
inferredcites →https://doi.org/10.1109/slt.2016.7846260openalex-snapshot
Deep neural network-based speaker embeddings for end-to-end speaker verification
inferredcites →https://doi.org/10.1109/slt.2018.8639585openalex-snapshot
Speaker Recognition from Raw Waveform with SincNet
inferredcites →https://doi.org/10.1109/sp.2017.49openalex-snapshot
Towards Evaluating the Robustness of Neural Networks
inferredcites →https://doi.org/10.1109/tasl.2010.2064307openalex-snapshot
Front-End Factor Analysis for Speaker Verification
inferredcites →https://doi.org/10.1109/tevc.2019.2890858openalex-snapshot
One Pixel Attack for Fooling Deep Neural Networks
inferredcites →https://doi.org/10.14722/ndss.2019.23288openalex-snapshot
Adversarial Attacks Against Automatic Speech Recognition Systems via Psychoacoustic Hiding
inferredcites →https://doi.org/10.24963/ijcai.2021/591openalex-snapshot
Recent Advances in Adversarial Training for Adversarial Robustness
inferredcites →https://doi.org/10.48550/arxiv.1708.09537openalex-snapshot
DolphinAtack: Inaudible Voice Commands
inferredcites →https://doi.org/10.48550/arxiv.1711.03280openalex-snapshot
Crafting Adversarial Examples For Speech Paralinguistics Applications
inferredcites →https://doi.org/10.48550/arxiv.1801.00554openalex-snapshot
Did you hear that? Adversarial Examples Against Automatic Speech Recognition
inferredcites →https://doi.org/10.48550/arxiv.1810.00069openalex-snapshot
Adversarial Attacks and Defences: A Survey
inferredcites →https://doi.org/10.48550/arxiv.1810.01268openalex-snapshot
CAAD 2018: Generating Transferable Adversarial Examples
inferredcites →https://doi.org/10.48550/arxiv.1811.09725openalex-snapshot
Interpretable Convolutional Filters with SincNet
inferredcites →https://doi.org/10.48550/arxiv.1906.06355openalex-snapshot
Perceptual Based Adversarial Audio Attacks
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/jsfa.12793openalex-snapshot
A tomato disease identification method based on leaf image automatic labeling algorithm and improved YOLOv5 model
inferred← citeshttps://doi.org/10.1007/s00521-025-11677-6openalex-snapshot
The asynchronous real-time universal adversarial perturbation generation method for practical speaker recognition systems
inferred← citeshttps://doi.org/10.1016/j.engappai.2023.107661openalex-snapshot
Speech and speaker recognition using raw waveform modeling for adult and children’s speech: A comprehensive review
inferred← citeshttps://doi.org/10.1016/j.ins.2022.05.092openalex-snapshot
Spatial-temporal interaction learning based two-stream network for action recognition
inferred← citeshttps://doi.org/10.1016/j.jvcir.2022.103632openalex-snapshot
Dual attention interactive fine-grained classification network based on data augmentation
inferred← citeshttps://doi.org/10.1016/j.neucom.2023.126436openalex-snapshot
Ensemble deep learning in speech signal tasks: A review
inferred← citeshttps://doi.org/10.1016/j.neucom.2025.131136openalex-snapshot
A survey of deep learning for face presentation attack detection
inferred← citeshttps://doi.org/10.1089/big.2021.0270openalex-snapshot
Predicting Social Events with Multimodal Fusion of Spatial and Temporal Dynamic Graph Representations
inferred← citeshttps://doi.org/10.1109/ipria53572.2021.9483536openalex-snapshot
Automatic Image Annotation using Tag Relations and Graph Convolutional Networks
inferred← citeshttps://doi.org/10.1145/3578585openalex-snapshot
Exploring the Effect of High-frequency Components in GANs Training
inferred← citeshttps://doi.org/10.1145/3587097openalex-snapshot
A 2 SC: Adversarial Attacks on Subspace Clustering
inferred← citeshttps://doi.org/10.1145/3587936openalex-snapshot
A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks
inferred← citeshttps://doi.org/10.1145/3616495openalex-snapshot
Contrastive Attention-guided Multi-level Feature Registration for Reference-based Super-resolution
inferred← citeshttps://doi.org/10.1145/3640817openalex-snapshot
MF 2 ShrT: Multimodal Feature Fusion Using Shared Layered Transformer for Face Anti-spoofing
inferred← citeshttps://doi.org/10.1145/3672563openalex-snapshot
Boosting Semi-Supervised Learning with Dual-Threshold Screening and Similarity Learning
inferred← citeshttps://doi.org/10.1145/3673657openalex-snapshot
TPTE: Text-Guided Patch Token Exploitation for Unsupervised Fine-Grained Representation Learning
inferred← citeshttps://doi.org/10.1145/3680207.3765246openalex-snapshot
MetaGuardian: Enhancing Voice Assistant Security through Advanced Acoustic Metamaterials
inferred← citeshttps://doi.org/10.1145/3686156openalex-snapshot
Target Structure Learning Framework for Unsupervised Multi-Class Domain Adaptation
inferred← citeshttps://doi.org/10.1145/3698773openalex-snapshot
Contrastive Learning-Based Speech Spoofing Detection for Multimedia Security in Edge Intelligence
inferred← citeshttps://doi.org/10.1145/3711867openalex-snapshot
Modeling Multi-modal Cross-interaction for Multi-label Few-shot Image Classification Based on Local Feature Selection
inferred← citeshttps://doi.org/10.1145/3722115openalex-snapshot
Multi-Modal Sarcasm Detection via Knowledge-Aware Focused Graph Convolutional Networks
inferred← citeshttps://doi.org/10.1186/s42400-025-00490-2openalex-snapshot
InfoShadow: NTK & MI guided adversarial attacks on speaker identification systems
inferred← citeshttps://doi.org/10.1561/116.00000017openalex-snapshot
An Application-Oriented Taxonomy on Spoofing, D isguise and Countermeasures in Speaker Recognition
inferred← citeshttps://doi.org/10.23919/cje.2025.00.174openalex-snapshot
Hierarchical Security Survey of Voice Control Systems: Vulnerabilities, Countermeasures, and Future Horizons
inferred← citeshttps://doi.org/10.3103/s1060992x23040021openalex-snapshot
Video Codec Using Machine Learning Based on Parametric Orthogonal Filters
inferred← citeshttps://doi.org/10.3390/app112110176openalex-snapshot
Deep Convolutional Neural Network with KNN Regression for Automatic Image Annotation
inferred← citeshttps://doi.org/10.3390/math12172736openalex-snapshot
A Multi-Branch Feature Extraction Residual Network for Lightweight Image Super-Resolution
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