Speaker-invariant Psychological Stress Detection Using Attention-based Network

International Conference
2020-12-01 16:58
Authors : Hyeon-Kyeong Shin, Hyewon Han, Kyungguen Byun, Hong-Goo Kang

Year : 2020

Publisher / Conference : APSIPA

Presentation/Publication date : 2020.12.08

Related project : 상대방의 감성을 추론, 판단하여 그에 맞추어 대화하고 대응할 수 있는 감성지능 기술 연구개발 (5/5)

Presentation : Oral

When people get stressed in nervous or unfamiliar situations, their speaking styles or acoustic characteristics change. These changes are particularly emphasized in certain regions of speech, so a model that automatically computes temporal weights for components of the speech signals that reflect stress-related information can effectively capture the psychological state of the speaker. In this paper, we propose an algorithm for psychological stress detection from speech signals using a deep spectral-temporal encoder and multi-head attention with domain adversarial training. To detect long-term variations and spectral relations in the speech under different stress conditions, we build a network by concatenating a convolutional neural network (CNN) and a recurrent neural network (RNN). Then, multi-head attention is utilized to further emphasize stress-concentrated regions. For speaker-invariant stress detection, the network is trained with adversarial multi-task learning by adding a gradient reversal layer. We show the robustness of our proposed algorithm in stress classification tasks on the Multimodal Korean stress database acquired in [1] and the authorized stress database Speech Under Simulated and Actual Stress (SUSAS) [2]. In addition, we demonstrate the effectiveness of multi-head attention and domain adversarial training with visualized analysis using the t-SNE method.
전체 327
317 International Conference Zainab Alhakeem, Yoohwan Kwon, Hong-Goo Kang "Disentangled Representations for Arabic Dialect Identification based on Supervised Clustering with Triplet Loss" in EUSIPCO, 2021
316 International Conference Miseul Kim, Minh-Tri Ho, Hong-Goo Kang "Self-supervised Complex Network for Machine Sound Anomaly Detection" in EUSIPCO, 2021
315 International Conference Kihyuk Jeong, Huu-Kim Nguyen, Hong-Goo Kang "A Fast and Lightweight Text-To-Speech Model with Spectrum and Waveform Alignment Algorithms" in EUSIPCO, 2021
314 International Conference Jiyoung Lee*, Soo-Whan Chung*, Sunok Kim, Hong-Goo Kang**, Kwanghoon Sohn** "Looking into Your Speech: Learning Cross-modal Affinity for Audio-visual Speech Separation" in CVPR, 2021
313 International Conference Zainab Alhakeem, Hong-Goo Kang "Confidence Learning from Noisy Labels for Arabic Dialect Identification" in ITC-CSCC, 2021
312 International Conference Huu-Kim Nguyen, Kihyuk Jeong, Hong-Goo Kang "Fast and Lightweight Speech Synthesis Model based on FastSpeech2" in ITC-CSCC, 2021
311 International Conference Yoohwan Kwon*, Hee-Soo Heo*, Bong-Jin Lee, Joon Son Chung "The ins and outs of speaker recognition: lessons from VoxSRC 2020" in ICASSP, 2021
310 International Conference You Jin Kim, Hee Soo Heo, Soo-Whan Chung, Bong-Jin Lee "End-to-end Lip Synchronisation Based on Pattern Classification" in IEEE Spoken Language Technology Workshop (SLT), 2020
309 International Conference Seong Min Kye, Yoohwan Kwon, Joon Son Chung "Cross Attentive Pooling for Speaker Verification" in IEEE Spoken Language Technology Workshop (SLT), 2020
308 International Conference Suhyeon Oh, Hyungseob Lim, Kyungguen Byun, Min-Jae Hwang, Eunwoo Song, Hong-Goo Kang "ExcitGlow: Improving a WaveGlow-based Neural Vocoder with Linear Prediction Analysis" in APSIPA (*awarded Best Paper), 2020