Speech emotion recognition using deep neural network and extreme learning machine.. Interspeech, 223--227, 2014. [PUMA: DNN, ELM, IEMOCAP, classification emotion recognition, speech]
Learning salient features for speech emotion recognition using convolutional neural networks. IEEE Transactions on Multimedia, (16)8:2203--2213, IEEE, 2014. [PUMA: CNN, DES, Emo-DB, MES, SAVEE, analysis, classification discriminative emotion feature learning, recognition, salient speech]
Improving automatic emotion recognition from speech via gender differentiation. Proc. Language Resources and Evaluation Conference (LREC 2006), Genoa, 2006. [PUMA: Berlin Emotion SmartKom, classification database differentiation, emotion emotional gender of recognition, speech speech,]
A Research of Speech Emotion Recognition Based on Deep Belief Network and SVM. Mathematical Problems in Engineering, (2014)Hindawi Publishing Corporation, 2014. [PUMA: SVM, belief classification deep emotion network, recognition, speech]
Speech emotion recognition using a deep autoencoder. Proceedings of the XV Reunión de Trabajo en Procesamiento de la Información y Control (RPIC 2013), San Carlos de Bariloche, 2013. [PUMA: Emo-DB, Multilayer autoencoder, classification emotion perceptron, recognition, speech]
Enhancing multilingual recognition of emotion in speech by language identification. Interspeech, 2016. [PUMA: EU-EMOSS, classification cross-lingual, emotion i-vector, identification, language multilingual, recognition, speech]
Domain adaptation for speech emotion recognition by sharing priors between related source and target classes. 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2608--2612, 2016. [PUMA: Domain adaptation, classification emotion nets, neural recognition, speech]
Emotions are a personal thing: Towards speaker-adaptive emotion recognition. 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 4803--4807, 2014. [PUMA: adaptive classification emotion identification, recognition, speaker speech]
i-Vector Algorithm with Gaussian Mixture Model for Efficient Speech Emotion Recognition. Computational Science and Computational Intelligence (CSCI), 2015 International Conference on, 476--480, 2015. [PUMA: GMM, IEMOCAP, MAP, UBM, classification emotion i-vector, recognition, speech]