most citedTwo-stage dimensional emotion recognition by fusing predictions of acoustic and text networks using SVM

46 citations · 143 across the 7 of their papers we have counts for

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eess.AS2020★ 14 cited

The Effect of Silence Feature in Dimensional Speech Emotion Recognition

Bagus Tris Atmaja, Masato Akagi

Silence is a part of human-to-human communication, which can be a clue for human emotion perception. For automatic emotion recognition by a computer, it is not clear whether silenc…

eess.AS2020★ 17 cited

Deep Multilayer Perceptrons for Dimensional Speech Emotion Recognition

Bagus Tris Atmaja, Masato Akagi

Modern deep learning architectures are ordinarily performed on high-performance computing facilities due to the large size of the input features and complexity of its model. This p…

eess.AS2020★ 21 cited

On The Differences Between Song and Speech Emotion Recognition: Effect of Feature Sets, Feature Types, and Classifiers

Bagus Tris Atmaja, Masato Akagi

In this paper, we evaluate the different features sets, feature types, and classifiers on both song and speech emotion recognition. Three feature sets: GeMAPS, pyAudioAnalysis, and…

eess.AS2020★ 42 cited

Multitask Learning and Multistage Fusion for Dimensional Audiovisual Emotion Recognition

Bagus Tris Atmaja, Masato Akagi

Due to its ability to accurately predict emotional state using multimodal features, audiovisual emotion recognition has recently gained more interest from researchers. This paper p…

eess.AS2020★ 3 cited

Evaluation of Error and Correlation-Based Loss Functions For Multitask Learning Dimensional Speech Emotion Recognition

Bagus Tris Atmaja, Masato Akagi

The choice of a loss function is a critical part of machine learning. This paper evaluated two different loss functions commonly used in regression-task dimensional speech emotion…