Wen Huang

Orcid: 0009-0004-3085-5795

Affiliations:
  • Shanghai Jiao Tong University, School of Electronic Information and Electrical Engineering, Shanghai, China


According to our database1, Wen Huang authored at least 11 papers between 2023 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2025
From Sharpness to Better Generalization for Speech Deepfake Detection.
CoRR, June, 2025

Data-Efficient Low-Complexity Acoustic Scene Classification via Distilling and Progressive Pruning.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

Generalizable Audio Deepfake Detection via Latent Space Refinement and Augmentation.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

SpeechFake: A Large-Scale Multilingual Speech Deepfake Dataset Incorporating Cutting-Edge Generation Methods.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024
Data-Efficient Low-Complexity Acoustic Scene Classification via Distilling and Progressive Pruning.
CoRR, 2024

Prototype and Instance Contrastive Learning for Unsupervised Domain Adaptation in Speaker Verification.
Proceedings of the 14th IEEE International Symposium on Chinese Spoken Language Processing, 2024

Improving Acoustic Scene Classification via Self-Supervised and Semi-Supervised Learning with Efficient Audio Transformer.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

Semi-Supervised Acoustic Scene Classification with Test-Time Adaptation.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

Robust Cross-Domain Speaker Verification with Multi-Level Domain Adapters.
Proceedings of the IEEE International Conference on Acoustics, 2024

Exploring Large Scale Pre-Trained Models for Robust Machine Anomalous Sound Detection.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
Improving Dino-Based Self-Supervised Speaker Verification with Progressive Cluster-Aware Training.
Proceedings of the IEEE International Conference on Acoustics, 2023


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