Andronic, Iustina;Kürzinger, Ludwig;Chavez Rosas, Edgar Ricardo;Rigoll, Gerhard;Seeber, Bernhard U.
MP3 Compression to Diminish Adversarial Noise in End-to-End Speech Recognition
Speech and Computer
Springer International Publishing
2020

Hiller, M., Kürzinger, L.; Sigl, G.
Review of error correction for PUFs and evaluation on state-of-the-art FPGAs
Journal of Cryptographic Engineering
2020
May

Kürzinger L., Watzel T., Li L., Baumgartner R., Rigoll G.
Exploring Hybrid CTC/Attention End-to-End Speech Recognition with Gaussian Processes
pp. 258-269
Proc. 21st International Conference on Speech and Computer SPECOM 2019
Lecture Notes in Computer Science
Springer
2019

Kürzinger, Ludwig;Chavez Rosas, Edgar Ricardo;Li, Lujun;Watzel, Tobias;Rigoll, Gerhard
Audio Adversarial Examples for Robust Hybrid CTC/Attention Speech Recognition
Speech and Computer
Springer International Publishing
2020

Kürzinger, Ludwig;Lindae, Nicolas;Klewitz, Palle;Rigoll, Gerhard
Lightweight End-to-End Speech Recognition from Raw Audio Data Using Sinc-Convolutions
Proc. Interspeech 2020
2020
Oct
1659--1663

Kürzinger, Ludwig;Winkelbauer, Dominik;Li, Lujun;Watzel, Tobias;Rigoll, Gerhard
CTC-Segmentation of Large Corpora for German End-to-End Speech Recognition
Speech and Computer
Springer International Publishing
2020

Li, Lujun;Kang, Yikai;Shi, Yuchen;Kürzinger, Ludwig;Watzel, Tobias;Rigoll, Gerhard
Adversarial Joint Training with Self-Attention Mechanism for Robust End-to-End Speech Recognition
arXiv preprint arXiv:2104.01471
2021

Li, Lujun;Kurzinger, Ludwig;Watzel, Tobias;Rigoll, Gerhard
A Global Discriminant Joint Training Framework for Robust Speech Recognition
2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI)
IEEE
2021

Li, Lujun;Lu, Zhenxing;Watzel, Tobias;Kürzinger, Ludwig;Rigoll, Gerhard
Light-Weight Self-Attention Augmented Generative Adversarial Networks for Speech Enhancement
Electronics
2021
10
13
1586

Li, Lujun;Watzel, Tobias;Kuerzinger, Ludwig;Rigoll, Gerhard
Towards Constructing HMM Structure for Speech Recognition With Deep Neural Fenonic Baseform Growing
IEEE Access
2021
9
39098--39110