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Nicolas M. Müller
Nicolas M. Müller
在 aisec.fraunhofer.de 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Does Audio Deepfake Detection Generalize?
NM Müller, P Czempin, F Dieckmann, A Froghyar, K Böttinger
Interspeech 2022, 2022
992022
Sc-glowtts: an efficient zero-shot multi-speaker text-to-speech model
E Casanova, C Shulby, E Gölge, NM Müller, FS de Oliveira, AC Junior, ...
InterSpeech 2021, 2021
792021
Speech is silver, silence is golden: What do asvspoof-trained models really learn?
NM Müller, F Dieckmann, P Czempin, R Canals, K Böttinger, J Williams
ASVspoof 2021, 2021
622021
Identifying Mislabeled Instances in Classification Datasets
NM Müller, K Markert
2019 International Joint Conference on Neural Networks (IJCNN), 2019
582019
Human perception of audio deepfakes
NM Müller, K Markert, J Williams
First International Workshop on Deepfake Detection for Audio Multimedia at …, 2021
562021
Data poisoning attacks on regression learning and corresponding defenses
N Müller, D Kowatsch, K Böttinger
2020 IEEE 25th Pacific Rim International Symposium on Dependable Computing …, 2020
232020
On GDPR compliance of companies’ privacy policies
NM Müller, D Kowatsch, P Debus, D Mirdita, K Böttinger
Text, Speech, and Dialogue: 22nd International Conference, TSD 2019 …, 2019
182019
Distributed Anomaly Detection of Single Mote Attacks in RPL Networks
N Müller, P Debus, DKK Böttinger
Proceedings of the 16th International Joint Conference on e-Business and …, 2019
172019
Attacker Attribution of Audio Deepfakes
NM Müller, F Dieckmann, J Williams
Interspeech 2022, 2022
122022
A. d. S. Soares, SM Aluisio, and MA Ponti,“Sc-glowtts: an efficient zero-shot multi-speaker text-to-speech model,”
E Casanova, C Shulby, E Gölge, NM Müller, FS de Oliveira, AC Junior
arXiv preprint arXiv:2104.05557, 2021
112021
Mlaad: The multi-language audio anti-spoofing dataset
NM Müller, P Kawa, WH Choong, E Casanova, E Gölge, T Müller, P Syga, ...
arXiv preprint arXiv:2401.09512, 2024
102024
Towards resistant audio adversarial examples
T Dörr, K Markert, NM Müller, K Böttinger
Proceedings of the 1st ACM Workshop on Security and Privacy on Artificial …, 2020
82020
Complex-valued neural networks for voice anti-spoofing
NM Müller, P Sperl, K Böttinger
arXiv preprint arXiv:2308.11800, 2023
62023
Harder or Different? Understanding Generalization of Audio Deepfake Detection
NM Müller, N Evans, H Tak, P Sperl, K Böttinger
arXiv preprint arXiv:2406.03512, 2024
12024
Shortcut Detection with Variational Autoencoders
NM Müller, S Roschmann, S Khan, P Sperl, K Böttinger
arXiv preprint arXiv:2302.04246, 2023
12023
Localized Shortcut Removal
NM Müller, J Jacobs, J Williams, K Böttinger
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
12023
Deep Reinforcement Learning for Backup Strategies against Adversaries
P Debus, N Müller, K Böttinger
arXiv preprint arXiv:2102.06632, 2021
12021
Adversarial vulnerability of active transfer learning
NM Müller, K Böttinger
Advances in Intelligent Data Analysis XIX: 19th International Symposium on …, 2021
12021
Defending against adversarial denial-of-service data poisoning attacks
NM Müller, S Roschmann, K Böttinger
Proceedings of the 2020 Workshop on DYnamic and Novel Advances in Machine …, 2020
12020
Easy, Interpretable, Effective: openSMILE for voice deepfake detection
O Pascu, D Oneata, H Cucu, NM Müller
arXiv preprint arXiv:2408.15775, 2024
2024
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