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Employing voice-based emotion recognition function in artificial intelligence (AI) product will improve the user experience.
“Bimodal recurrent neural network for audiovisual voice activity detection,”
F. Tao and C. Busso, · 1942
Earlier work this paper cites.
“Recognizing emotion in speech,”
F. Dellaert and T. Polzin A. Waibel, · 1973
Earlier work this paper cites.
“Hidden Markov model-based speech emotion recognition,”
B. Schuller, G. Rigoll, and M. Lang, · 2003
Earlier work this paper cites.
“Analysis of emotion recognition using facial expressions, speech and multimodal information,”
C. Busso, Z. Deng, S. Yildirim, M. Bulut, C.M. Lee, A. Kazemzadeh, S. Lee, U. Neumann, and S. Narayanan, · 2004
Earlier work this paper cites.
“Emotion recognition based on phoneme classes,”
C.M. Lee, S. Yildirim, M. Bulut, A. Kazemzadeh, C. Busso, Z. Deng, S. Lee, and S.S. Narayanan, · 2004
Earlier work this paper cites.
“A fast learning algorithm for deep belief nets,”
G. Hinton, S. Osindero, and Y. Teh, · 2006
Earlier work this paper cites.
“The INTERSPEECH 2010 paralinguistic challenge,”
B. Schuller, S. Steidl, A. Batliner, F. Burkhardt, L. Devillers, C. Muller, and S. Narayanan, · 2010
Earlier work this paper cites.
“On-line emotion recognition in a 3-D activation-valence-time continuum using acoustic and linguistic cues,”
F. Eyben, M. Wöllmer, A. Graves, B. Schuller, E. Douglas-Cowie, and R. Cowie, · 2010
Earlier work this paper cites.
“Front-end factor analysis for speaker verification,”
N. Dehak, P.J. Kenny, R. Dehak, P. Dumouchel, and P. Ouellet, · 2010
Earlier work this paper cites.
“Libshorttext: A library for short-text classification and analysis,”
H. Yu, C. Ho, Y. Juan, and C. Lin, · 2013
Cited alongside, same era.
“Lipreading approach for isolated digits recognition under whisper and neutral speech.,”
F. Tao and C. Busso, · 2014
Cited alongside, same era.
“Speech emotion recognition with acoustic and lexical features,”
Q. Jin, C. Li, S. Chen, and H. Wu, · 2015
Cited alongside, same era.
“A time delay neural network architecture for efficient modeling of long temporal contexts.,”
V. Peddinti, D. Povey, and S. Khudanpur, · 2015
Cited alongside, same era.
“MEC 2016: The multimodal emotion recognition challenge of ccpr 2016,”
Y. Li, J. Tao, B. Schuller, S. Shan, D. Jiang, and J. Jia, · 2016
Cited alongside, same era.
“Dbn-ivector framework for acoustic emotion recognition.,”
R. Xia and Y. Liu, · 2016
“Fisher kernels on phase-based features for speech emotion recognition,”
J. Deng, X. Xu, Z. Zhang, S. Frühholz, D. Grandjean, and B. Schuller, · 2017
Later among the works it cites.
“Automatic speech emotion recognition using recurrent neural networks with local attention,”
S. Mirsamadi, E. Barsoum, and C. Zhang, · 2017
Later among the works it cites.
“A multi-task learning framework for emotion recognition using 2d continuous space,”
R. Xia and Y. Liu, · 2017
Later among the works it cites.
“Jointly predicting arousal, valence and dominance with multi-task learning,”
S. Parthasarathy and C. Busso, · 2017
Later among the works it cites.
“Focal,” https://sites.google.com/site/nikobrummer/focal, 2017,
Niko Brummer, · 2017
Later among the works it cites.
“The opensesame NIST 2016 speaker recognition evaluation system,”
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Cited alongside, same era.
“Recurrent neural networks for polyphonic sound event detection in real life recordings,”
G. Parascandolo, H. Huttunen, and T. Virtanen, · 2016
Cited alongside, same era.
“End-to-end attention-based large vocabulary speech recognition,”
Dzmitry D. Bahdanau, J. Chorowski, D. Serdyuk, and Yoshua Y. Bengio, · 2016
Cited alongside, same era.
G. Liu, Q. Qian, Z. Wang, Q. Zhao, T. Wang, H. Li, J. Xue, S. Zhu, R. Jin, and T. Zhao, · 2017
Later among the works it cites.
“Convolutional recurrent neural networks for polyphonic sound event detection,”
E. Cakir, G. Parascandolo, T. Heittola, H. Huttunen, and T. Virtanen, · 2017
Later among the works it cites.
“Advanced LSTM: A study about better time dependency modeling in emotion recognition,”
F. Tao and G. Liu, · 2017
Later among the works it cites.