1. S. -H. Fang, P. -H. Li, H. -H. Jung and S. -S. Wang, "Geometrically-informed Graph Neural Networks for Distributed Speech Enhancement in Challenging Acoustic Environments," in IEEE Sensors Letters, doi: 10.1109/LSENS.2025.3564309. keywords: {Microphones;Noise;Speech enhancement;Graph neural networks;Meters;Recording;Program processors;Noise measurement;Feature extraction;Training;Distributed speech enhancement;graph neural network;distributed microphone;geometirc informed;interpretability},
  2. S. -S. Wang, J. -Y. Chen, B. -R. Bai, S. -H. Fang and Y. Tsao, "Unsupervised Face-Masked Speech Enhancement Using Generative Adversarial Networks With Human-in-the-Loop Assessment Metrics," in IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 32, pp. 3826-3837, 2024, doi: 10.1109/TASLP.2024.3426996. keywords: {Speech enhancement;Noise;Generators;Noise measurement;Measurement;Training;Recording;Face-masked speech enhancement;generative adversarial networks;human-in-the-loop;StarGAN;unsupervised learning},
  3. C.-T. Wang, T.-M. Chen, N.-T. Lee, and S.-H. Fang, “Development of an explainable artificial intelligence-based prediction model for glottic neoplasm using deep learning on laryngoscopic images,” The Laryngoscope, vol. 134, no. 11, pp. 4585–4592, Nov. 2024, doi: 10.1002/lary.31563.
  4. G. Liu, R. Xie, S. -H. Fang, H. -C. Wu and K. Yan, "Novel Human-Posture Recognition System Based on Advanced Graph Convolutional Network Using Skeletal Data," in IEEE Journal of Selected Areas in Sensors, vol. 1, pp. 224-236, 2024, doi: 10.1109/JSAS.2024.3475355. keywords: {Feature extraction;Sensors;Data mining;Sensor phenomena and characterization;Long short term memory;Image segmentation;Image recognition;Cameras;Videos;Graph convolutional networks;Automatic segmentation of skeletal data;graph convolutional network (GCN);human-posture recognition;Kinect V2 sensor;skeletal graph},
  5. S. -S. Wang, C. -C. Tsai, W. -C. Yu and S. -H. Fang, "A Lightweight Learning Framework for Packet Loss Concealment and Speech Enhancement," in IEEE Transactions on Cognitive Communications and Networking, doi: 10.1109/TCCN.2024.3482355. keywords: {Speech enhancement;Packet loss;Speech processing;Receivers;Noise;Training;Signal processing algorithms;Robustness;Noise measurement;Delays;Packet loss concealment;speech enhancement;fully convolutional network;interpolation-based post-filter;low-latency online communication},
  6. K. Yan et al., "Novel Subject-Dependent Human-Posture Recognition Approach Using Tensor Regression," in IEEE Sensors Journal, vol. 25, no. 1, pp. 1041-1053, 1 Jan.1, 2025, doi: 10.1109/JSEN.2024.3493893. keywords: {Deep learning;Training;Support vector machines;Tensors;Codes;Three-dimensional displays;One shot learning;Feature extraction;Transformers;Vectors;Dynamic multidimensional time-series segmentation;human-posture recognition Kinect data;skeletal graph;tensor regression},
  7. Tsai, Cheng-Yuan, Sheng-Chain Chang, Chao-Hsiang Hung, Syu-Siang Wang, and Shih-Hau Fang. 2024. "Improved Speech Authenticity Detection in Chinese–English Bilingual Contexts" Sensors 24, no. 21: 6807. https://doi.org/10.3390/s24216807

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