12 citations · 12 across the 3 of their papers we have counts for
3 papers
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…
eess.AS2022
Jointly Predicting Emotion, Age, and Country Using Pre-Trained Acoustic Embedding
Bagus Tris Atmaja, Zanjabila, Akira Sasou
In this paper, we demonstrated the benefit of using pre-trained model to extract acoustic embedding to jointly predict (multitask learning) three tasks: emotion, age, and native co…