Auditory-Inspired End-to-End Speech Emotion Recognition Using 3D Convolutional Recurrent Neural Networks Based on Spectral-Temporal Representation

Zhichao Peng, Zhi Zhu, Masashi Unoki, Jianwu Dang, Masato Akagi. Auditory-Inspired End-to-End Speech Emotion Recognition Using 3D Convolutional Recurrent Neural Networks Based on Spectral-Temporal Representation. In 2018 IEEE International Conference on Multimedia and Expo, ICME 2018, San Diego, CA, USA, July 23-27, 2018. pages 1-6, IEEE Computer Society, 2018. [doi]

@inproceedings{PengZUDA18,
  title = {Auditory-Inspired End-to-End Speech Emotion Recognition Using 3D Convolutional Recurrent Neural Networks Based on Spectral-Temporal Representation},
  author = {Zhichao Peng and Zhi Zhu and Masashi Unoki and Jianwu Dang and Masato Akagi},
  year = {2018},
  doi = {10.1109/ICME.2018.8486564},
  url = {http://doi.ieeecomputersociety.org/10.1109/ICME.2018.8486564},
  researchr = {https://researchr.org/publication/PengZUDA18},
  cites = {0},
  citedby = {0},
  pages = {1-6},
  booktitle = {2018 IEEE International Conference on Multimedia and Expo, ICME 2018, San Diego, CA, USA, July 23-27, 2018},
  publisher = {IEEE Computer Society},
  isbn = {978-1-5386-1737-3},
}