MuSe 2022 Challenge-Reference-Cited by-同舟云学术

MuSe 2022 Challenge

Published:2022-10-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 30th ACM International Conference on Multimedia
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Author:

Amiriparian Shahin¹,Christ Lukas¹,König Andreas²,Meßner Eva-Maria³,Cowen Alan⁴,Cambria Erik⁵,Schuller Björn W.⁶

Affiliation:

1. University of Augsburg, Augsburg, Germany

2. University of Passau, Passau, Germany

3. University of Ulm, Ulm, Germany

4. Hume AI, New York, NY, USA

5. Nanyang Technological University, Singapore, Singapore

6. Imperial College London, London, United Kingdom

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3503161.3551792

Reference12 articles.

1. Shahin Amiriparian Nicholas Cummins Sandra Ottl Maurice Gerczuk and Björn Schuller. 2017. Sentiment Analysis Using Image-based Deep Spectrum Features. In Proceedings 2nd International Workshop on Automatic Sentiment Analysis in the Wild (WASA 2017) held in conjunction with the 7th biannual Conference on Affective Computing and Intelligent Interaction (ACII 2017). AAAC IEEE San Antonio TX 26--29. Shahin Amiriparian Nicholas Cummins Sandra Ottl Maurice Gerczuk and Björn Schuller. 2017. Sentiment Analysis Using Image-based Deep Spectrum Features. In Proceedings 2nd International Workshop on Automatic Sentiment Analysis in the Wild (WASA 2017) held in conjunction with the 7th biannual Conference on Affective Computing and Intelligent Interaction (ACII 2017). AAAC IEEE San Antonio TX 26--29.

2. Towards cross-modal pre-training and learning tempo-spatial characteristics for audio recognition with convolutional and recurrent neural networks

3. DeepSpectrumLite: A Power-Efficient Transfer Learning Framework for Embedded Speech and Audio Processing From Decentralized Data

4. Erik Cambria , Dipankar Das , Sivaji Bandyopadhyay , and Antonio Feraco . 2017. Affective computing and sentiment analysis . In A practical guide to sentiment analysis . Springer , 1--10. Erik Cambria, Dipankar Das, Sivaji Bandyopadhyay, and Antonio Feraco. 2017. Affective computing and sentiment analysis. In A practical guide to sentiment analysis. Springer, 1--10.

5. Stress detection in daily life scenarios using smart phones and wearable sensors: A survey

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