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Presentation #	7
Session:	Detection, Paralinguistics and Coding
Session Time:	Wednesday, December 19, 13:30 - 15:30
Presentation Time:	Wednesday, December 19, 13:30 - 15:30
Presentation:	Poster
Topic:	Emotion recognition from speech:
Paper Title:	CONTEXT-AWARE ATTENTION MECHANISM FOR SPEECH EMOTION RECOGNITION
Authors:	Gaetan Ramet; Ecole Polytechnique Federale de Lausanne
	Philip N. Garner; Idiap Research Institute
	Michael Baeriswyl; Swisscom
	Alexandros Lazaridis; Swisscom
Abstract:	In this work, we study the use of attention mechanisms to enhance the performance of the state-of-the-art deep learning model in Speech Emotion Recognition (SER). We introduce a new Long Short-Term Memory (LSTM)-based neural attention model which is able to take into account the temporal information in speech during the computation of the attention vector. The proposed LSTM-based model is evaluated on the IEMOCAP dataset using a 5-fold cross-validation scheme and achieved 68.8% weighted accuracy on 4 classes, which outperforms other state-of-the-art models.