Published in IEEE ICASSP, 2021
In this paper, we proposed a self-supervised augmentation defense (SSAD) model that can defend against different adversarial attacks without knowing the types beforehand.
Recommended citation: Under Review." IEEE ICASSP2022.. 1(1).
Published in IEEE Signal Processing Magazine, 2021
This paper is providing a tutorial of the current techniques applied to speech emotion recognition (SER), which is divided into three major components including Robustness, Generalization, and Usability. In this paper, readers could quickly follow up and conduct the hands-on experiment with the provided example guiding.
Recommended citation: Lee, C. C., Sridhar, K., Li, J. L., Lin, W. C., Su, B. H., & Busso, C. (2021). "Deep Representation Learning for Affective Speech Signal Analysis and Processing: Preventing unwanted signal disparities." IEEE Signal Processing Magazine, 38(6), 22-38. 1(1). https://ieeexplore.ieee.org/abstract/document/9591505
Published in ISCA Interspeech, 2021
To protect the privacy issue of end-users, we design a flexible attribute align strategy for distributing the information according to the pre-defined order. The overall architecture is implemented integrating the concept of dropout function and achieving the competitive results while considering the privacy compared to the SOTA.
Recommended citation: Huang, Y. L., Su, B. H., Hong, Y. W. P., & Lee, C. C. (2021). "An Attribute-Aligned Strategy for Learning Speech Representation." arXiv preprint arXiv:2106.02810. 1(1). https://www.isca-speech.org/archive/pdfs/interspeech_2021/huang21b_interspeech.pdf
Published in IEEE Spoken Language Technology Workshop (SLT), 2021
Recommended citation: Su, B. H., & Lee, C. C. (2021, January). "A Conditional Cycle Emotion Gan for Cross Corpus Speech Emotion Recognition." In 2021 IEEE Spoken Language Technology Workshop (SLT) (pp. 351-357). IEEE. 1(1). https://ieeexplore.ieee.org/document/9383512
Published in ISCA Interspeech, 2020
Recommended citation: Zhong, S. C., Su, B. H., Huang, W., Liu, Y. C., & Lee, C. C. (2020). "Predicting Collaborative Task Performance using Graph Interlocutor Acoustic Network in Small Group Interaction." In INTERSPEECH (pp. 3122-3126). IEEE. 1(1). http://www.interspeech2020.org/uploadfile/pdf/Wed-3-3-2.pdf
Published in ISCA Interspeech, 2020
Recommended citation: Su, B. H., Chang, C. M., Lin, Y. S., & Lee, C. C. (2020). "Improving Speech Emotion Recognition Using Graph Attentive Bi-directional Gated Recurrent Unit Network." In INTERSPEECH (pp. 506-510). 1(1). http://www.interspeech2020.org/uploadfile/pdf/Mon-2-1-3.pdf
Published in ISCA Interspeech, 2020
Recommended citation: Upadhyay, S. G., Su, B. H., & Lee, C. C. (2020). "Attentive Convolutional Recurrent Neural Network Using Phoneme-Level Acoustic Representation for Rare Sound Event Detection." In INTERSPEECH (pp. 3102-3106). 1(1). http://www.interspeech2020.org/uploadfile/pdf/Wed-3-2-8.pdf
Published in ISCA Interspeech, 2019
Recommended citation: S.-L. Yeh, G.-Y. Chao, B.-H. Su, Y.-L. Huang, M.-H. Lin, C.-K. Lee, and C.-C. Lee (2019). "Using Attention Networks and Adversarial Augmentation for Styrian Dialect Continuous Sleepiness and Baby Sound Recognition." In Interspeech (pp. 2398-2402). 1(1). https://www.researchgate.net/profile/Bo-Su-17/publication/335829696_Using_Attention_Networks_and_Adversarial_Augmentation_for_Styrian_Dialect_Continuous_Sleepiness_and_Baby_Sound_Recognition/links/5df7001792851c836480bb43/Using-Attention-Networks-and-Adversarial-Augmentation-for-Styrian-Dialect-Continuous-Sleepiness-and-Baby-Sound-Recognition.pdf
Published in ISCA Interspeech, 2019
Recommended citation: Su, B. H., Yeh, S. L., Ko, M. Y., Chen, H. Y., Zhong, S. C., Li, J. L., & Lee, C. C. (2018). "Self-Assessed Affect Recognition Using Fusion of Attentional BLSTM and Static Acoustic Features." In Interspeech (pp. 536-540). 1(1). https://www.isca-speech.org/archive_v0/Interspeech_2018/pdfs/2261.pdf
Published in IEEE ACII, 2017
Recommended citation: Chang, C. M., Su, B. H., Lin, S. C., Li, J. L., & Lee, C. C. (2017, October). "Bootstrapped Multi-View Weighted Kernel Fusion Framework for Cross-Corpus Integration of Multimodal Emotion Recognition." In 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII) (pp. 377-382). IEEE. 1(1). https://ieeexplore.ieee.org/document/8273627