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20202024
most citedTwo-stage dimensional emotion recognition by fusing predictions of acoustic and text networks using SVM

46 citations · 92 across the 9 of their papers we have counts for

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12 papers · 1 filter

eess.AS2024

Uncertainty-Based Ensemble Learning For Speech Classification

Bagus Tris Atmaja, Felix Burkhardt

Speech classification has attracted increasing attention due to its wide applications, particularly in classifying physical and mental states. However, these tasks are challenging…

eess.AS2023

Ensembling Multilingual Pre-Trained Models for Predicting Multi-Label Regression Emotion Share from Speech

Bagus Tris Atmaja, Akira Sasou

Speech emotion recognition has evolved from research to practical applications. Previous studies of emotion recognition from speech have focused on developing models on certain dat…

eess.AS2022★ 4 cited

Effect of different splitting criteria on the performance of speech emotion recognition

Bagus Tris Atmaja, Akira Sasou

Traditional speech emotion recognition (SER) evaluations have been performed merely on a speaker-independent condition; some of them even did not evaluate their result on this cond…

eess.AS2022★ 3 cited

Predicting Affective Vocal Bursts with Finetuned wav2vec 2.0

Bagus Tris Atmaja, Akira Sasou

The studies of predicting affective states from human voices have relied heavily on speech. This study, indeed, explores the recognition of humans' affective state from their vocal…

eess.AS2022

Cross-dataset COVID-19 Transfer Learning with Cough Detection, Cough Segmentation, and Data Augmentation

Bagus Tris Atmaja, Zanjabila, Suyanto +1

This paper addresses issues on cough-based COVID-19 detection. We propose a cross-dataset transfer learning approach to improve the performance of COVID-19 detection by incorporati…

eess.AS2022★ 12 cited

Comparing Hysteresis Comparator and RMS Threshold Methods for Automatic Single Cough Segmentations

Bagus Tris Atmaja, Zanjabila, Suyanto +1

Research on diagnosing diseases based on voice signals currently are rapidly increasing, including cough-related diseases. When training the cough sound signals into deep learning…