Time-Frequency Transformer: A Novel Time Frequency Joint Learning Method for Speech Emotion Recognition-Reference-Cited by-同舟云学术

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Time-Frequency Transformer: A Novel Time Frequency Joint Learning Method for Speech Emotion Recognition

Published:2023-11-26 Issue: Volume: Page:415-427
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Wang Yong,Lu Cheng,Zong Yuan,Lian Hailun,Zhao Yan,Li Sunan

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-8138-0_33

Reference29 articles.

1. Schuller, B., Batliner, A.: Computational Paralinguistics: Emotion, Affect and Personality in Speech and Language Processing. John Wiley & Sons (2013)

2. Schuller, B.W.: Speech emotion recognition: two decades in a nutshell, benchmarks, and ongoing trends. Commun. ACM 61(5), 90–99 (2018)

3. Akçay, M.B., Oğuz, K.: Speech emotion recognition: emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers. Speech Commun. 116, 56–76 (2020)

4. Lu, C., Zong, Y., Zheng, W., Li, Y., Tang, C., Schuller, B.W.: Domain invariant feature learning for speaker-independent speech emotion recognition. IEEE/ACM Trans. Audio Speech Lang. Process. 30, 2217–2230 (2022)

5. Stuhlsatz, A., Meyer, C., Eyben, F., Zielke, T., Meier, G., Schuller, B.: Deep neural networks for acoustic emotion recognition: raising the benchmarks. In: 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5688–5691. IEEE (2011)

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1. Speech Swin-Transformer: Exploring a Hierarchical Transformer with Shifted Windows for Speech Emotion Recognition;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

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