Exploring Hybrid CTC/Attention End-to-End Speech Recognition with Gaussian Processes. - Ludwig Kürzinger; Tobias Watzel; Lujun Li 002; Robert Baumgartner; Gerhard Rigoll (SPECOM, 2019)

Deep Neural Network Quantizers Outperforming Continuous Speech Recognition Systems. - Tobias Watzel; Lujun Li 002; Ludwig Kürzinger; Gerhard Rigoll (SPECOM, 2019)

Audio Adversarial Examples for Robust Hybrid CTC/Attention Speech Recognition. - Ludwig Kürzinger; Edgar Ricardo Chavez Rosas; Lujun Li 002; Tobias Watzel; Gerhard Rigoll (SPECOM, 2020)

CTC-Segmentation of Large Corpora for German End-to-End Speech Recognition. - Ludwig Kürzinger; Dominik Winkelbauer; Lujun Li 002; Tobias Watzel; Gerhard Rigoll (SPECOM, 2020)

Synchronized Forward-Backward Transformer for End-to-End Speech Recognition. - Tobias Watzel; Ludwig Kürzinger; Lujun Li 002; Gerhard Rigoll (SPECOM, 2020)

A Global Discriminant Joint Training Framework for Robust Speech Recognition. - Lujun Li 002; Ludwig Kürzinger; Tobias Watzel; Gerhard Rigoll (ICTAI, 2021)

Regularized Forward-Backward Decoder for Attention Models. - Tobias Watzel; Ludwig Kürzinger; Lujun Li 002; Gerhard Rigoll (SPECOM, 2021)

Induced Local Attention for Transformer Models in Speech Recognition. - Tobias Watzel; Ludwig Kürzinger; Lujun Li 002; Gerhard Rigoll (SPECOM, 2021)

Towards Constructing HMM Structure for Speech Recognition With Deep Neural Fenonic Baseform Growing. - Lujun Li 002; Tobias Watzel; Ludwig Kürzinger; Gerhard Rigoll (IEEE Access, 2021)

Adversarial joint training with self-attention mechanism for robust end-to-end speech recognition. - Lujun Li 002; Yikai Kang; Yuchen Shi; Ludwig Kürzinger; Tobias Watzel; Gerhard Rigoll (EURASIP J. Audio Speech Music. Process., 2021)

Enhancements for Hybrid and End-to-End Speech Recognition Architectures (Erweiterungen für hybride und Ende-zu-Ende Spracherkennungssysteme) - Tobias Watzel (2023)