Domain Adversarial for Acoustic Emotion Recognition
Abdelwahab, Mohammed; Busso, Carlos;
Subject: Electrical Engineering and Systems Science - Audio and Speech Processing | Computer Science - Sound
The performance of speech emotion recognition is affected by the differences in data distributions between train (source domain) and test (target domain) sets used to build and evaluate the models. This is a common problem, as multiple studies have shown that the perfor... View more
 C. Busso, M. Bulut, and S.S. Narayanan, “Toward effective automatic recognition systems of emotion in speech,” in Social emotions in nature and artifact: emotions in human and human-computer interaction, J. Gratch and S. Marsella, Eds., pp. 110-127. Oxford University Press, New York, NY, USA, November 2013.
 Y. Kim and E. Mower Provost, “Say cheese vs. smile: Reducing speechrelated variability for facial emotion recognition,” in ACM International Conference on Multimedia (MM 2014), Orlando, FL, USA, November 2014, pp. 27-36.
 D. Ververidis and C. Kotropoulos, “Automatic speech classification to five emotional states based on gender information,” in European Signal Processing Conference (EUSIPCO 2004), Vienna, Austria, September 2004, pp. 341-34.
 T. Vogt and E. Andre´, “Comparing feature sets for acted and spontaneous speech in view of automatic emotion recognition,” in IEEE International Conference on Multimedia and Expo (ICME 2005), Amsterdam, The Netherlands, July 2005, pp. 474-477.
 S. Parthasarathy and C. Busso, “Jointly predicting arousal, valence and dominance with multi-task learning,” in Interspeech 2017, Stockholm, Sweden, August 2017, pp. 1103-1107.
 M. Abdelwahab and C. Busso, “Ensemble feature selection for domain adaptation in speech emotion recognition,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017), New Orleans, LA, USA, March 2017, pp. 5000-5004.
 M. Abdelwahab and C. Busso, “Incremental adaptation using active learning for acoustic emotion recognition,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017), New Orleans, LA, USA, March 2017, pp. 5160-5164.
 Y. Zong, W. Zheng, T. Zhang, and X. Huang, “Cross-corpus speech emotion recognition based on domain-adaptive least-squares regression,” IEEE Signal Processing Letters, vol. 23, no. 5, pp. 585-589, May 2016.
 M. Abdelwahab and C. Busso, “Supervised domain adaptation for emotion recognition from speech,” in International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2015), Brisbane, Australia, April 2015, pp. 5058-5062.
 T. Rahman and C. Busso, “A personalized emotion recognition system using an unsupervised feature adaptation scheme,” in International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2012), Kyoto, Japan, March 2012, pp. 5117-5120.