| Speech enhancement and dereverberation with diffusion-based generative models J Richter, S Welker, JM Lemercier, B Lay, T Gerkmann IEEE/ACM Transactions on Audio, Speech, and Language Processing 31, 2351-2364, 2023 | 134 | 2023 |
| Speech enhancement with score-based generative models in the complex STFT domain S Welker, J Richter, T Gerkmann ISCA Interspeech, 2022 | 86 | 2022 |
| Storm: A diffusion-based stochastic regeneration model for speech enhancement and dereverberation JM Lemercier, J Richter, S Welker, T Gerkmann IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2023 | 56 | 2023 |
| Analysing diffusion-based generative approaches versus discriminative approaches for speech restoration JM Lemercier, J Richter, S Welker, T Gerkmann ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 27 | 2023 |
| Speech enhancement with stochastic temporal convolutional networks J Richter, G Carbajal, T Gerkmann ISCA Interspeech, 4516-4520, 2020 | 27 | 2020 |
| Guided variational autoencoder for speech enhancement with a supervised classifier G Carbajal, J Richter, T Gerkmann ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 19 | 2021 |
| Reducing the prior mismatch of stochastic differential equations for diffusion-based speech enhancement B Lay, S Welker, J Richter, T Gerkmann ISCA Interspeech, 2023 | 17 | 2023 |
| Disentanglement learning for variational autoencoders applied to audio-visual speech enhancement G Carbajal, J Richter, T Gerkmann 2021 IEEE Workshop on Applications of Signal Processing to Audio and …, 2021 | 16 | 2021 |
| Audio-visual speech separation in noisy environments with a lightweight iterative model H Martel, J Richter, K Li, X Hu, T Gerkmann arXiv preprint arXiv:2306.00160, 2023 | 7 | 2023 |
| Causal Diffusion Models for Generalized Speech Enhancement J Richter, S Welker, JM Lemercier, B Lay, T Peer, T Gerkmann IEEE Open Journal of Signal Processing, 2024 | 6 | 2024 |
| Diffusion Models for Audio Restoration JM Lemercier, J Richter, S Welker, E Moliner, V Välimäki, T Gerkmann arXiv preprint arXiv:2402.09821, 2024 | 6 | 2024 |
| Audio-visual speech enhancement with score-based generative models J Richter, S Frintrop, T Gerkmann Speech Communication; 15th ITG Conference, 275-279, 2023 | 6 | 2023 |
| Speech signal improvement using causal generative diffusion models J Richter, S Welker, JM Lemercier, B Lay, T Peer, T Gerkmann ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 4 | 2023 |
| The PESQetarian: On the Relevance of Goodhart's Law for Speech Enhancement D de Oliveira, S Welker, J Richter, T Gerkmann arXiv preprint arXiv:2406.03460, 2024 | 3 | 2024 |
| Single and few-step diffusion for generative speech enhancement B Lay, JM Lermercier, J Richter, T Gerkmann ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 3 | 2024 |
| EARS: An Anechoic Fullband Speech Dataset Benchmarked for Speech Enhancement and Dereverberation J Richter, YC Wu, S Krenn, S Welker, B Lay, S Watanabe, A Richard, ... arXiv preprint arXiv:2406.06185, 2024 | 2 | 2024 |
| On the Behavior of Intrusive and Non-intrusive Speech Enhancement Metrics in Predictive and Generative Settings D de Oliveira, J Richter, JM Lemercier, T Peer, T Gerkmann Speech Communication; 15th ITG Conference, 260-264, 2023 | 2 | 2023 |
| Continuous phoneme recognition based on audio-visual modality fusion J Richter, J Liebold, T Gerkamnn 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 2 | 2022 |
| Improving mix-and-separate training in audio-visual sound source separation with an object prior Q Nguyen, J Richter, M Lauri, T Gerkmann, S Frintrop 2020 25th International Conference on Pattern Recognition (ICPR), 5844-5851, 2021 | 2 | 2021 |
| Investigating Training Objectives for Generative Speech Enhancement J Richter, D de Oliveira, T Gerkmann arXiv preprint arXiv:2409.10753, 2024 | | 2024 |
Timo GerkmannSignal Processing, Computer Science Department, Universität Hamburg, Germany在 uni-hamburg.de 的电子邮件经过验证
