|Title:||A Segment Level Approach to Speech Emotion Recognition Using Transfer Learning|
Pratim Roy, Partha
Sanniti di Baja G.
|Published in:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
5th Asian Conference on Pattern Recognition, ACPR 2019
|Abstract:||Speech emotion recognition (SER) is a non-trivial task considering that the very definition of emotion is ambiguous. In this paper, we propose a speech emotion recognition system that predicts emotions for multiple segments of a single audio clip unlike the conventional emotion recognition models that predict the emotion of an entire audio clip directly. The proposed system consists of a pre-trained deep convolutional neural network (CNN) followed by a single layered neural network which predicts the emotion classes of the audio segments. The predictions for the individual segments are finally combined to predict the emotion of a particular clip. We define several new types of accuracies while evaluating the performance of the proposed model. The proposed model attains an accuracy of 68.7% surpassing the current state-of-the-art models in classifying the data into one of the four emotional classes (angry, happy, sad and neutral) when trained and evaluated on IEMOCAP audio-only dataset. © 2020, Springer Nature Switzerland AG.|
|Citation:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2020), 12047 LNCS: 435-448|
|Author Scopus IDs:||57215662056|
|Author Affiliations:||Sahoo, S., Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, 600036, India|
Kumar, P., Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India
Raman, B., Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India
Roy, P.P., Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India
|Corresponding Author:||Sahoo, S.; Department of Electrical Engineering, India; email: email@example.com|
|Appears in Collections:||Conference Publications [CS]|
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