End-To-End Label Uncertainty Modeling for Speech-based Arousal Recognition Using Bayesian Neural Networks

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. In Hanseok Ko, John H. L. Hansen, editors, Interspeech 2022, 23rd Annual Conference of the International Speech Communication Association, Incheon, Korea, 18-22 September 2022. pages 151-155, ISCA, 2022. [doi]

@inproceedings{PrabhuCLG22,
  title = {End-To-End Label Uncertainty Modeling for Speech-based Arousal Recognition Using Bayesian Neural Networks},
  author = {Navin Raj Prabhu and Guillaume Carbajal and Nale Lehmann-Willenbrock and Timo Gerkmann},
  year = {2022},
  doi = {10.21437/Interspeech.2022-10490},
  url = {https://doi.org/10.21437/Interspeech.2022-10490},
  researchr = {https://researchr.org/publication/PrabhuCLG22},
  cites = {0},
  citedby = {0},
  pages = {151-155},
  booktitle = {Interspeech 2022, 23rd Annual Conference of the International Speech Communication Association, Incheon, Korea, 18-22 September 2022},
  editor = {Hanseok Ko and John H. L. Hansen},
  publisher = {ISCA},
}