Yuqin Lin (林羽钦)

Yuqin Lin (林羽钦)

Assistant Professor with the College of Computer and Data Science, Fuzhou University, China

Publications

You can also find my articles on my Google Scholar profile.

Journal Articles (期刊论文)

  1. Wang, X.,Wen, B., Wei, X., Lin, Y., Li, K., Cao, Y., Wang, T., Gu, M., Jiang, Y., Li, J., Wang, Long., & Dang, J. (2026). LPM-Aug: Latent pathology-informed multimodal augmentation for generalized cognitive decline detection via speech. IEEE Transactions on Affective Computing. （中科院一区TOP，IF: 18.5） [Paper]
  2. Lin, Y., Wang, L., Dang, J., & Minematsu, N. (2025). Gestural feature extraction and multi-feature co-activation for dysarthric speech recognition. Information Fusion, 103490. （中科院一区TOP，IF: 15.5） [Paper]
  3. Lin, Y., Wang, L., Yang, Y., & Dang, J. (2023). CFDRN: A cognition-inspired feature decomposition and recombination network for dysarthric speech recognition. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 31, 3824-3836. （中科院一区） [Paper]
  4. Lin, Y., Dang, J., Wang, L., Li, S., & Ding, C. (2023). Disordered speech recognition considering low resources and abnormal articulation. Speech Communication, 155, 103002.（中科院二区，CCF-B） [Paper]
  5. Lin, Y., Zhang, S., Gao, Z., Wang, L., Yang, Y., & Dang, J. (2023). Wav2vec‐MoE: An unsupervised pre‐training and adaptation method for multi‐accent ASR. Electronics Letters, 59(11), e12823.（高贡献作者奖） [Paper]

Conference Papers （国际会议论文）

  1. Lin, Y., Zhang, J., Wei, X., Li, K., Wen, B., Gu, M., & Dang, J. (2026). MCI-OTFusion: A multimodal model for MCI detection and cognitive score prediction. Proc. IEEE-ICASSP, pp. 15557-15561. [Paper]
  2. Wei, X., Wen, B., Lin, Y., Li, K., Wang, X., Wang, Long., & Dang, J. (2026). Breaking data efficiency dilemma: A federated and augmented learning framework for Alzheimer's disease detection via speech. Proc. IEEE-ICASSP, pp. 19147-19151. [Paper]
  3. Lin, Y., Wang, L., Dang, J., & Minematsu, N. (2024). Exploring pre-trained speech model for articulatory feature extraction in dysarthric speech using ASR. Proc. INTERSPEECH, pp. 1-5. [Paper]
  4. Yang, Y., Shi, H., Lin, Y., Ge, M., Wang, L., Hou, Q., & Dang, J. (2022). Adaptive attention network with domain adversarial training for multi-accent speech recognition. IEEE-ISCSLP, pp. 6-10. [Paper]
  5. Qin, S., Wang, L., Li, S., Lin, Y., & Dang, J. (2022). Finer-grained modeling units-based meta-Learning for low-resource Tibetan speech recognition. Proc. INTERSPEECH, pp. 2133-2137. [Paper]
  6. Xu, Q., Song, T., Wang, L., Shi, H., Lin, Y., Lv, Y., ... & Dang, J. (2022). Self-distillation based on high-level information supervision for compressing end-to-end ASR model. Proc. INTERSPEECH, pp. 1716-1720. [Paper]
  7. Song T, Xu Q., Ge M., Wang L., Shi H., Lv Y., Lin Y., Dang J. (2022). Language-specific characteristic assistance for code-switching speech recognition. Proc. INTERSPEECH, pp. 3924-3928. [Paper]
  8. Lin, Y., Wang, L., Dang, J., Li, S., & Ding, C. (2020). End-to-end articulatory modeling for dysarthric articulatory attribute detection. In Proc. IEEE-ICASSP, pp. 7349-7353. [Paper]
  9. Lin, Y., Wang, L., Li, S., Dang, J., & Ding, C. (2020). Staged knowledge distillation for end-to-end dysarthric speech recognition and speech attribute transcription. Proc. INTERSPEECH, pp. 4791-4795. [Paper]