| End-to-end label uncertainty modeling for speech-based arousal recognition using bayesian neural networks NR Prabhu, G Carbajal, N Lehmann-Willenbrock, T Gerkmann Proc. Interspeech 2022, 151--155, 2021 | 12 | 2021 |
| Defining and quantifying conversation quality in spontaneous interactions N Raj Prabhu, C Raman, H Hung Companion Publication of the 2020 International Conference on Multimodal …, 2020 | 12 | 2020 |
| Leveraging semantic information for efficient self-supervised emotion recognition with audio-textual distilled models D de Oliveira, NR Prabhu, T Gerkmann Proc. Interspeech 2023, 3632--3636, 2023 | 4 | 2023 |
| Label uncertainty modeling and prediction for speech emotion recognition using t-distributions NR Prabhu, N Lehmann-Willenbrock, T Gerkmann 2022 10th International Conference on Affective Computing and Intelligent …, 2022 | 4 | 2022 |
| Perceived conversation quality in spontaneous interactions C Raman, NR Prabhu, H Hung IEEE Transactions on Affective Computing, 2023 | 2 | 2023 |
| EMOCONV-Diff: Diffusion-Based Speech Emotion Conversion for Non-Parallel and in-the-Wild Data NR Prabhu, B Lay, S Welker, N Lehmann-Willenbrock, T Gerkmann ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 1 | 2024 |
| In-the-wild speech emotion conversion using disentangled self-supervised representations and neural vocoder-based resynthesis NR Prabhu, N Lehmann-Willenbrock, T Gerkmann Speech Communication; 15th ITG Conference, 176-180, 2023 | 1 | 2023 |
| End-to-end label uncertainty modeling in speech emotion recognition using bayesian neural networks and label distribution learning NR Prabhu, N Lehmann-Willenbrock, T Gerkmann IEEE Transactions on Affective Computing, 2023 | 1 | 2023 |
| Conversation Quality: Modeling in Free-Standing Conversational Groups N Raj Prabhu Delft University of Technology, 2020 | | 2020 |
Timo GerkmannSignal Processing, Computer Science Department, Universität Hamburg, GermanyVerified email at uni-hamburg.de
