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ORCIDNavin Raj Prabhu
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2020 – today
- 2024
[j2]Navin Raj Prabhu
, Nale Lehmann-Willenbrock, Timo Gerkmann:
End-to-End Label Uncertainty Modeling in Speech Emotion Recognition Using Bayesian Neural Networks and Label Distribution Learning. IEEE Trans. Affect. Comput. 15(2): 579-592 (2024)- [c5]Navin Raj Prabhu, Bunlong Lay, Simon Welker, Nale Lehmann-Willenbrock, Timo Gerkmann:
EMOCONV-Diff: Diffusion-Based Speech Emotion Conversion for Non-Parallel and in-the-Wild Data. ICASSP 2024: 11651-11655 - [i9]Navin Raj Prabhu, Maria Tsfasman, Catharine Oertel, Timo Gerkmann, Nale Lehmann-Willenbrock:
Dynamics of Collective Group Affect: Group-level Annotations and the Multimodal Modeling of Convergence and Divergence. CoRR abs/2409.08578 (2024) - 2023
- [j1]Chirag Raman, Navin Raj Prabhu, Hayley Hung:
Perceived Conversation Quality in Spontaneous Interactions. IEEE Trans. Affect. Comput. 14(4): 2901-2912 (2023) - [c4]Danilo de Oliveira, Navin Raj Prabhu, Timo Gerkmann:
Leveraging Semantic Information for Efficient Self-Supervised Emotion Recognition with Audio-Textual Distilled Models. INTERSPEECH 2023: 3632-3636 - [i8]Danilo de Oliveira, Navin Raj Prabhu, Timo Gerkmann:
Leveraging Semantic Information for Efficient Self-Supervised Emotion Recognition with Audio-Textual Distilled Models. CoRR abs/2305.19184 (2023) - [i7]Navin Raj Prabhu, Nale Lehmann-Willenbrock, Timo Gerkmann:
In-the-wild Speech Emotion Conversion Using Disentangled Self-Supervised Representations and Neural Vocoder-based Resynthesis. CoRR abs/2306.01916 (2023) - [i6]Navin Raj Prabhu, Bunlong Lay, Simon Welker, Nale Lehmann-Willenbrock, Timo Gerkmann:
EMOCONV-DIFF: Diffusion-based Speech Emotion Conversion for Non-parallel and In-the-wild Data. CoRR abs/2309.07828 (2023) - 2022
- [c3]Navin Raj Prabhu, Nale Lehmann-Willenbrock, Timo Gerkmann:
Label Uncertainty Modeling and Prediction for Speech Emotion Recognition using t-Distributions. ACII 2022: 1-8 - [c2]Navin Raj Prabhu, Guillaume Carbajal, Nale Lehmann-Willenbrock, Timo Gerkmann:
End-To-End Label Uncertainty Modeling for Speech-based Arousal Recognition Using Bayesian Neural Networks. INTERSPEECH 2022: 151-155 - [i5]Chirag Raman, Navin Raj Prabhu, Hayley Hung:
Perceived Conversation Quality in Spontaneous Interactions. CoRR abs/2207.05791 (2022) - [i4]Navin Raj Prabhu, Nale Lehmann-Willenbrock, Timo Gerkmann:
Label Uncertainty Modeling and Prediction for Speech Emotion Recognition using t-Distributions. CoRR abs/2207.12135 (2022) - [i3]Navin Raj Prabhu, Nale Lehmann-Willenbrock, Timo Gerkmann:
End-to-End Label Uncertainty Modeling in Speech Emotion Recognition using Bayesian Neural Networks and Label Distribution Learning. CoRR abs/2209.15449 (2022) - 2021
- [i2]Navin Raj Prabhu, Guillaume Carbajal, Nale Lehmann-Willenbrock, Timo Gerkmann:
End-to-end label uncertainty modeling for speech emotion recognition using Bayesian neural networks. CoRR abs/2110.03299 (2021) - 2020
- [c1]Navin Raj Prabhu, Chirag Raman, Hayley Hung:
Defining and Quantifying Conversation Quality in Spontaneous Interactions. ICMI Companion 2020: 196-205 - [i1]Navin Raj Prabhu, Chirag Raman, Hayley Hung:
Defining and Quantifying Conversation Quality in Spontaneous Interactions. CoRR abs/2009.12842 (2020)
Coauthor Index
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