Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Sasou, Akira"'
Autor:
Atmaja, Bagus Tris, Sasou, Akira
Speech emotion recognition has evolved from research to practical applications. Previous studies of emotion recognition from speech have focused on developing models on certain datasets like IEMOCAP. The lack of data in the domain of emotion modeling
Externí odkaz:
http://arxiv.org/abs/2309.11014
Autor:
Atmaja, Bagus Tris, Sasou, Akira
Publikováno v:
TENCON 2021, pp 760-764
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 condition. This paper highlights the importance of splitting training and
Externí odkaz:
http://arxiv.org/abs/2210.14501
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 incorporating cough detection, cough segmentation, and data augmentation. The fir
Externí odkaz:
http://arxiv.org/abs/2210.05843
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 models, it is necessary to have a standard input by segmenting several
Externí odkaz:
http://arxiv.org/abs/2210.02057
Autor:
Atmaja, Bagus Tris, Sasou, Akira
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 burst, a short non-verbal vocalization. Borrowing the idea from the r
Externí odkaz:
http://arxiv.org/abs/2209.13146
Publikováno v:
International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) 2022
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 country. The pre-trained model was trained with wav2vec 2.0 large robust
Externí odkaz:
http://arxiv.org/abs/2207.10333
Publikováno v:
In Speech Communication May 2022 140:11-28
Autor:
Atmaja, Bagus Tris1 (AUTHOR) b-atmaja@aist.go.jp, Sasou, Akira1 (AUTHOR)
Publikováno v:
Sensors (14248220). Sep2022, Vol. 22 Issue 17, p6369. 11p.
Autor:
Atmaja, Bagus Tris1,2 (AUTHOR) b-atmaja@aist.go.jp, Sasou, Akira1 (AUTHOR)
Publikováno v:
Sensors (14248220). Aug2022, Vol. 22 Issue 16, p5941-5941. 14p.