Imperial College London
Alternate

STEFANOS ZAFEIRIOU, PhD

Faculty of Engineering, Department of Computing

Professor in Machine Learning & Computer Vision
 
 
 
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Contact

 

+44 (0)20 7594 8461s.zafeiriou Website CV

 
 
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Location

 

375Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Trigeorgis:2016:10.1109/ICASSP.2016.7472669,
author = {Trigeorgis, G and Ringeval, F and Brückner, R and Marchi, E and Nicolaou, M and Schuller, B and Zafeiriou, S},
doi = {10.1109/ICASSP.2016.7472669},
publisher = {IEEE},
title = {Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network},
url = {http://dx.doi.org/10.1109/ICASSP.2016.7472669},
year = {2016}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - The automatic recognition of spontaneous emotions from speech is a challenging task. On the one hand, acoustic features need to be robust enough to capture the emotional content for various styles of speaking, and while on the other, machine learning algorithms need to be insensitive to outliers while being able to model the context. Whereas the latter has been tackled by the use of Long Short-Term Memory (LSTM) networks, the former is still under very active investigations, even though more than a decade of research has provided a large set of acoustic descriptors. In this paper, we propose a solution to the problem of `context-aware' emotional relevant feature extraction, by combining Convolutional Neural Networks (CNNs) with LSTM networks, in order to automatically learn the best representation of the speech signal directly from the raw time representation. In this novel work on the so-called end-to-end speech emotion recognition, we show that the use of the proposed topology significantly outperforms the traditional approaches based on signal processing techniques for the prediction of spontaneous and natural emotions on the RECOLA database.
AU  - Trigeorgis,G
AU  - Ringeval,F
AU  - Brückner,R
AU  - Marchi,E
AU  - Nicolaou,M
AU  - Schuller,B
AU  - Zafeiriou,S
DO  - 10.1109/ICASSP.2016.7472669
PB  - IEEE
PY  - 2016///
TI  - Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network
UR  - http://dx.doi.org/10.1109/ICASSP.2016.7472669
UR  - https://ieeexplore.ieee.org/document/7472669
UR  - http://hdl.handle.net/10044/1/32349
ER  -
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