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Applications in Music and Audio Processing (MLR-MUSI)

Emotion Classification: How Does an Automated System Compare to Naive Human Coders?


The fact that emotions play a vital role in social interactions, along with the demand for novel human-computer interaction applications, have led to the development of a number of automatic emotion classification systems. However, it is still debatable whether the performance of such systems can compare with human coders. To address this issue, in this study, we present a comprehensive comparison in a speech-based emotion classification task between 138 Amazon Mechanical Turk workers (Turkers) and a state-of-the-art automatic computer system.

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Authors:
Kenneth Imade, Na Yang, Melissa Sturge-Apple, Zhiyao Duan, Wendi Heinzelman
Submitted On:
17 March 2016 - 3:26pm
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[1] Kenneth Imade, Na Yang, Melissa Sturge-Apple, Zhiyao Duan, Wendi Heinzelman, "Emotion Classification: How Does an Automated System Compare to Naive Human Coders?", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/747. Accessed: Sep. 16, 2019.
@article{747-16,
url = {http://sigport.org/747},
author = {Kenneth Imade; Na Yang; Melissa Sturge-Apple; Zhiyao Duan; Wendi Heinzelman },
publisher = {IEEE SigPort},
title = {Emotion Classification: How Does an Automated System Compare to Naive Human Coders?},
year = {2016} }
TY - EJOUR
T1 - Emotion Classification: How Does an Automated System Compare to Naive Human Coders?
AU - Kenneth Imade; Na Yang; Melissa Sturge-Apple; Zhiyao Duan; Wendi Heinzelman
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/747
ER -
Kenneth Imade, Na Yang, Melissa Sturge-Apple, Zhiyao Duan, Wendi Heinzelman. (2016). Emotion Classification: How Does an Automated System Compare to Naive Human Coders?. IEEE SigPort. http://sigport.org/747
Kenneth Imade, Na Yang, Melissa Sturge-Apple, Zhiyao Duan, Wendi Heinzelman, 2016. Emotion Classification: How Does an Automated System Compare to Naive Human Coders?. Available at: http://sigport.org/747.
Kenneth Imade, Na Yang, Melissa Sturge-Apple, Zhiyao Duan, Wendi Heinzelman. (2016). "Emotion Classification: How Does an Automated System Compare to Naive Human Coders?." Web.
1. Kenneth Imade, Na Yang, Melissa Sturge-Apple, Zhiyao Duan, Wendi Heinzelman. Emotion Classification: How Does an Automated System Compare to Naive Human Coders? [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/747

Feature Adapted Convolutional Neural Networks for Downbeat Tracking

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Authors:
Durand, S. and Bello, J. P and Bertrand, D. and Richard, G.
Submitted On:
14 March 2016 - 2:03pm
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[1] Durand, S. and Bello, J. P and Bertrand, D. and Richard, G., "Feature Adapted Convolutional Neural Networks for Downbeat Tracking", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/678. Accessed: Sep. 16, 2019.
@article{678-16,
url = {http://sigport.org/678},
author = {Durand; S. and Bello; J. P and Bertrand; D. and Richard; G. },
publisher = {IEEE SigPort},
title = {Feature Adapted Convolutional Neural Networks for Downbeat Tracking},
year = {2016} }
TY - EJOUR
T1 - Feature Adapted Convolutional Neural Networks for Downbeat Tracking
AU - Durand; S. and Bello; J. P and Bertrand; D. and Richard; G.
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/678
ER -
Durand, S. and Bello, J. P and Bertrand, D. and Richard, G.. (2016). Feature Adapted Convolutional Neural Networks for Downbeat Tracking. IEEE SigPort. http://sigport.org/678
Durand, S. and Bello, J. P and Bertrand, D. and Richard, G., 2016. Feature Adapted Convolutional Neural Networks for Downbeat Tracking. Available at: http://sigport.org/678.
Durand, S. and Bello, J. P and Bertrand, D. and Richard, G.. (2016). "Feature Adapted Convolutional Neural Networks for Downbeat Tracking." Web.
1. Durand, S. and Bello, J. P and Bertrand, D. and Richard, G.. Feature Adapted Convolutional Neural Networks for Downbeat Tracking [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/678

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