arXiv subjects

Shuqiong Wu

Publications and source records attributed to Shuqiong Wu.

4 recordsLinked to original sources

arXiv2026

AdoDAS: A Privacy-Preserving Multimodal Challenge for Adolescent Depression, Anxiety, and Stress Assessment

Adolescent depression, anxiety, and stress (D/A/S) call for scalable tools that complement, rather than replace, professional evaluation. Under a privacy-preserving policy, the AdoDAS Grand Challenge withholds minors' raw recordings and distributes anonymized audio-visual representations and ASR-derived text. Its 6,000 participants provide 24,000 segments across one scripted-reading and three open-response sessions. Two tracks assess multi-task binary D/A/S screening and ordinal prediction of 21 DASS-21 item responses. From 191 registrations, the final leaderboards included 95 eligible screening teams and 64 item-prediction teams. Audio-visual baselines achieved 0.4604 mean F1 and 0.2675 mean Quadratic Weighted Kappa; leading submissions reached 0.5921 and 0.2776. Representative systems emphasize cross-session modelling, temporal multimodal fusion, psychometric structure, and task-aware calibration.

cs.MM↗

arXiv2026

AcoustEmo: Open-Vocabulary Emotion Reasoning via Utterance-Aware Acoustic Q-Former

Multimodal Large Language Models (MLLMs) excel in Open-Vocabulary (OV) emotion recognition but often neglect fine-grained acoustic modeling. Existing methods typically use global audio encoders, failing to capture subtle, local temporal dynamics like micro-prosody and intonation shifts within individual utterances. To address this, we propose AcoustEmo, a time-sensitive MLLM featuring a novel Utterance-Aware Acoustic Q-Former. Our approach utilizes a timestamp-synchronized sliding window to dynamically extract segment-level audio tokens instead of coarse global representations. This enables the model to explicitly trace the temporal evolution of subtle acoustic clues and capture deep contextual dependencies in dialogues. Experiments on the Explainable Multimodal Emotion Recognition (EMER) task show that AcoustEmo significantly enhances complex emotion reasoning, outperforming baselines while maintaining robust contextual accuracy.

cs.MM↗

arXiv2024

Radar-based Measurement of the Body Movements of Multiple Students in Classroom Environments

We demonstrate the feasibility of the radar-based measurement of body movements in scenarios involving multiple students using a pair of 79-GHz millimeter-wave radar systems with array antennas. We quantify the body motion using the Doppler frequency calculated from radar echoes. The measurement accuracy is evaluated for two experimental scenarios, namely university students in an office and elementary school students in a classroom. The body movements measured using the two radar systems are compared to evaluate the repeatability and angle dependency of the measurement. Moreover, in the first scenario, we compare the radar-estimated body movement with subjective evaluation scores provided by two evaluators. In the first scenario, the coefficient of correlation between the radar-estimated body movement and the subjective evaluation score is 0.73 on average, with a maximum value of 0.97; in the second scenario, the average correlation coefficient of body movements measured using two radar systems is as high as 0.78. These results indicate that the proposed approach can be used to monitor the body movements of multiple students in realistic scenarios.

eess.SP↗

arXiv2020

Two-dimensional Ultrasound Imaging Technique based on Neural Network using Acoustic Simulation

The two-dimensional (2D) ultrasound imaging is widely used in several fields. In this study, the potential of two-dimensional ultrasound imaging technique based on machine learning is shown. A line transmitter was placed at one side and a receiver array was placed at the opposite side of the medium, respectively. The received signals at the receiver array was considered as a 2D image and it was converted to a 2D geometry of the target medium using convolutional neural network (CNN). The results of the numerical simulation studies which use up to 40000 simulation data showed the good agreement between the estimated and true geometry.

physics.med-ph↗