清华大学 Wei-Qiang Zhang--Home--Selected Conference Publications

Wei-Qiang Zhang

Name (Simplified Chinese):Wei-Qiang Zhang
Name (English):Wei-Qiang Zhang
E-Mail:
School/Department:Department of Electronic Engineering
Business Address:Room 5-111, Rohm Building
Contact Information:+86-10-62781847
Degree:Doctoral degree
Alma Mater:Tsinghua University
Teacher College:DZGCX
Discipline:Signal and Information Processing

Contact Information

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Selected Conference Publications

Y. Pu and W.-Q. Zhang, “Integrating pause information with word embeddings in language models for Alzheimer’s disease detection from spontaneous speech,” in Proc. ICASSP, 2025. doi: 10.1109/ICASSP49660.2025.10888563.
Z. Wan, Z. Qiu, Y. Liu, and W.-Q. Zhang, “Metadata-enhanced speech emotion recognition: Augmented residual integration and co-attention in two-stage fine-tuning,” in Proc. ICASSP, 2025. doi: 10.1109/ICASSP49660.2025.10890812.
Z. Chen, Y.-F. Shao, Y. Ma, M. Wei, L. Zhang, and W.-Q. Zhang, “Improving acoustic scene classification in low-resource conditions,” in Proc. ICASSP, 2025. doi: 10.1109/ICASSP49660.2025.10888928.
A. Jiang, X. Zheng, B. Han, Y. Qiu, P. Fan, W.-Q. Zhang, L. Cheng, and J. Liu, “Adaptive prototype learning for anomalous sound detection with partially known attributes,” in Proc. ICASSP, 2025. doi: 10.1109/ICASSP49660.2025.10889514.
B. Han, W. Huang, Z. Chen, A. Jiang, P. Fan, L. Cheng, Z. Lv, J. Liu, W.-Q. Zhang, and Y. Qian, “Data-efficient low-complexity acoustic scene classification via distilling and progressive pruning,” in Proc. ICASSP, 2025. doi: 10.1109/ICASSP49660.2025.10890296.
K. Pang, M. Bai, J. Yang, W.-Q. Zhang, M. Jiang, and Y. Huang, “Winstega: An adaptive robust enhancement framework for generative linguistic steganography,” in Proc. ICASSP, 2025. doi: 10.1109/ICASSP49660.2025.10888944.
B. Han, Z. Lv, A. Jiang, W. Huang, Z. Chen, Y. Deng, J. Ding, C. Lu, W.-Q. Zhang, P. Fan, J. Liu, and Y. Qian, “Exploring large scale pre-trained models for robust machine anomalous sound detection,” in Proc. ICASSP, 2024, pp. 1327–1330. doi: 10.1109/ICASSP48485.2024.10447183.
J. Li and W.-Q. Zhang, “Whisper-based transfer learning for Alzheimer disease classification: Leveraging speech segments with full transcripts as prompts,” in Proc. ICASSP, 2024, pp. 11211–11215. doi: 10.1109/ICASSP48485.2024.10448004.
H. Wang, G. Hu, G. Lin, W.-Q. Zhang, and J. Li, “Simul-Whisper: Attention-guided streaming Whisper with truncation detection,” in Proc. Interspeech, 2024, pp. 4483–4487. doi: 10.21437/Interspeech.2024-1814.
J. Li, Y. Pu, Q. Sun, and W.-Q. Zhang, “Improving Whisper’s recognition performance for under-represented language Kazakh leveraging unpaired speech and text,” in Proc. Interspeech, 2024, pp. 2514–2518. doi: 10.21437/Interspeech.2024-1790.
A. Jiang, B. Han, Z. Lv, Y. Deng, W.-Q. Zhang, X. Chen, Y. Qian, J. Liu, and P. Fan, “AnoPatch: Towards better consistency in machine anomalous sound detection,” in Proc. Interspeech, 2024, pp. 107–111. doi: 10.21437/Interspeech.2024-1761.
X. Zheng, A. Jiang, B. Han, Y. Qian, P. Fan, J. Liu, and W.-Q. Zhang, “Improving anomalous sound detection via low-rank adaptation fine-tuning of pre-trained audio models,” in Proc. SLT, 2024, pp. 979–984. doi: 10.1109/SLT61566.2024.10832335.
A. Jiang, Y. Shi, P. Fan, W.-Q. Zhang, and J. Liu, “CoopASD: Cooperative machine anomalous sound detection with privacy concerns,” in Proc. GLOBECOM, 2024, pp. 346–351. doi: 10.1109/GLOBECOM52923.2024.10901774.
X. Chen, Y. Pu, J. Li, and W.-Q. Zhang, “Cross-lingual Alzheimer’s disease detection based on paralinguistic and pre-trained features,” in Proc. ICASSP, 2023. doi: 10.1109/ICASSP49357.2023.10095522.
A. Jiang, W.-Q. Zhang, Y. Deng, P. Fan, and J. Liu, “Unsupervised anomaly detection and localization of machine audio: A GAN-based approach,” in Proc. ICASSP, 2023. doi: 10.1109/ICASSP49357.2023.10096813.
H. Wang, S. Wang, W.-Q. Zhang, and J. Bai, “DistilXLSR: A light weight cross-lingual speech representation model,” in Proc. Interspeech, 2023, pp. 2273–2277. doi: 10.21437/Interspeech.2023-1444.
H. Wang, S. Wang, W.-Q. Zhang, H. Suo, and Y. Wan, “Task-agnostic structured pruning of speech representation models,” in Proc. Interspeech, 2023, pp. 231–235. doi: 10.21437/Interspeech.2023-1442.
Z. Cui, W. Wu, C. Zhang, W.-Q. Zhang, and J. Wu, “Transferring speech-generic and depression-specific knowledge for Alzheimer’s disease detection,” in Proc. ASRU, 2023. doi: 10.1109/ASRU57964.2023.10389785.
Y. Wang, C. Tang, Z. Ma, Z. Zheng, X. Chen, and W.-Q. Zhang, “Exploring effective distillation of self-supervised speech models for automatic speech recognition,” in Proc. ASRU, 2023. doi: 10.1109/ASRU57964.2023.10389746.
Q. Hou, A. Jiang, W.-Q. Zhang, P. Fan, and J. Liu, “Decoupling detectors for scalable anomaly detection in AIoT systems with multiple machines,” in Proc. GLOBECOM, 2023, pp. 5943–5948. doi: 10.1109/GLOBECOM54140.2023.10436800.
J. Zhao, H. Wang, J. Li, S. Chai, G. Wang, G. Chen, and W.-Q. Zhang, “The THUEE system description for the IARPA OpenASR21 challenge,” in Proc. Interspeech, 2022. doi: 10.21437/Interspeech.2022-269.
J. Zhao, G. Shi, G.-B. Wang, and W.-Q. Zhang, “Automatic speech recognition for low-resource languages: The THUEE systems for the IARPA OpenASR20 evaluation,” in Proc. ASRU, 2021, pp. 335–341. doi: 10.1109/ASRU51503.2021.9688260.
L. Xue, K. Song, D. Wu, X. Tan, N. L. Zhang, T. Qin, W.-Q. Zhang, and T.-Y. Liu, “DeepRapper: Neural rap generation with rhyme and rhythm modeling,” in Proc. ACL, 2021, pp. 69-81. doi: 10.18653/v1/2021.acl-long.6.
G. Chen, S. Chai, G. Wang, J. Du, W.-Q. Zhang, C. Weng, D. Su, D. Povey, J. Trmal, J. Zhang, M. Jin, S. Khudanpur, S. Watanabe, S. Zhao, W. Zou, X. Li, X. Yao, Y. Wang, Y. Wang, Z. You, and Z. Yan, “GigaSpeech: An evolving, multi-domain ASR corpus with 10,000 hours of transcribed audio,” in Proc. Interspeech, 2021, pp. 3670-3674. doi: 10.21437/Interspeech.2021-1965.
J. Zhao, Z. Lv, A. Han, G. Wang, G. Shi, J. Kang, J. Yan, P. Hu, S. Huang, and W.-Q. Zhang, “The TNT team system descriptions of Cantonese and Mongolian for IARPA OpenASR20,” in Proc. Interspeech, 2021, pp. 4344-4348. doi: 10.21437/Interspeech.2021-1063.
H. Yu, J. Zhao, S. Yang, Z. Wu, Y. Nie, and W.-Q. Zhang, “Language recognition based on unsupervised pretrained models,” in Proc. Interspeech, 2021, pp. 3271-3275. doi: 10.21437/Interspeech.2021-807.
Y. Yan, X. Tan, B. Li, G. Zhang, T. Qin, S. Zhao, Y. Shen, W.-Q. Zhang, and T.-Y. Liu, “Adaptive text to speech for spontaneous style,” in Proc. Interspeech, 2021, pp. 4668-4672. doi: 10.21437/Interspeech.2021-584.
K. He, Y. Shen, W.-Q. Zhang, and J. Liu, “Staged training strategy and multi-activation for audio tagging with noisy and sparse multi-label data,” in Proc. ICASSP, 2020, pp. 631-635. doi: 10.1109/ICASSP40776.2020.9053776.
J. Xie, R. Yan, S. Xiao, L. Peng, M. T. Johnson, and W.-Q. Zhang, “Dynamic temporal residual learning for speech recognition,” in Proc. ICASSP, 2020, pp. 7709-7713. doi: 10.1109/ICASSP40776.2020.9054653.
Z. Zhao and W.-Q. Zhang, “End-to-end keyword search based on attention and energy scorer for low resource languages,” in Proc. Interspeech, 2020, pp. 2587-2591. doi: 10.21437/Interspeech.2020-2613.
R. Li, T. Liang, D. Song, Y. Liu, Y. Wu, C. Xu, P. Ouyang, X. Zhang, X. Chen, W.-Q. Zhang, S. Yin, and L. He, “THUEE system for NIST SRE19 CTS challenge,” in Proc. Interspeech, 2020, pp. 2232-2236. doi: 10.21437/Interspeech.2020-1245.
Z. Li, L. He, J. Li, L. Wang, and W.-Q. Zhang, “Towards discriminative representations and unbiased predictions: Class-specific angular softmax for speech emotion recognition,” in Proc. Interspeech, 2019, pp. 1696-1700. doi: 10.21437/Interspeech.2019-1683.
K. He, Y. Shen, and W.-Q. Zhang, “Hierarchical pooling structure for weakly labeled sound event detection,” in Proc. Interspeech, 2019, pp. 3624-3628. doi: 10.21437/Interspeech.2019-2049.
H. Yang and W.-Q. Zhang, “Music genre classification using duplicated convolutional layers in neural networks,” in Proc. Interspeech, 2019, pp. 3382-3386. doi: 10.21437/Interspeech.2019-1298.
Y. Shen, K. He, and W.-Q. Zhang, “Learning how to listen: A temporal-frequential attention model for sound event detection,” in Proc. Interspeech, 2019, pp. 2563-2567. doi: 10.21437/Interspeech.2019-2045.
J. Kang, W.-Q. Zhang, and J. Liu, “Gated convolutional networks based hybrid acoustic models for low resource speech recognition,” in Proc. ASRU, 2017, pp. 157-164. doi: 10.1109/ASRU.2017.8268930.
Z.-Q. Lv, J. Kang, W.-Q. Zhang, and J. Liu, “An LSTM-CTC based verification system for proxy-word based OOV keyword search,” in Proc. ICASSP, 2017, pp. 5655-5659. doi: 10.1109/ICASSP.2017.7953239.
Y. Tian, L. He, M. Cai, W.-Q. Zhang, and J. Liu, “Deep neural networks based speaker modeling at different levels of phonetic granularity,” in Proc. ICASSP, 2017, pp. 5440-5444. doi: 10.1109/ICASSP.2017.7953196.
X.-K. Yang, D. Qu, W.-L. Zhang, and W.-Q. Zhang, “The NDSC transcription system for the 2016 multi-genre broadcast challenge,” in Proc. SLT, 2016, pp. 273-278. doi: 10.1109/SLT.2016.7846276.
Z.-Q. Lv, M. Cai, W.-Q. Zhang, and J. Liu, “A novel discriminative score calibration method for keyword search,” in Proc. Interspeech, 2016, pp. 745-749. doi: 10.21437/Interspeech.2016-606.
Y. Tian, M. Cai, H. Liang, W.-Q. Zhang, and J. Liu, “Improving deep neural networks based speaker verification using unlabeled data,” in Proc. Interspeech, 2016, pp. 1863-1867. doi: 10.21437/Interspeech.2016-614.
Z.-Q. Lv, M. Cai, C. Lu, J. Kang, L.-K. Hui, W.-Q. Zhang, and J. Liu, “Improved system fusion for keyword search,” in Proc. ASRU, 2015, pp. 231-236. doi: 10.1109/ASRU.2015.7404799.
M. Cai, Z.-Q. Lv, B.-L. Song, Y.-Z. Shi, W.-L. Wu, C. Lu, W.-Q. Zhang, and J. Liu, “The THUEE system for the OpenKWS14 keyword search evaluation,” in Proc. ICASSP, 2015, pp. 4734-4738. doi: 10.1109/ICASSP.2015.7178869.
J. Kang, C. Lu, M. Cai, W.-Q. Zhang, and J. Liu, “Neuron sparseness versus connection sparseness in deep neural network for large vocabulary speech recognition,” in Proc. ICASSP, 2015, pp. 4954-4958. doi: 10.1109/ICASSP.2015.7178913.
Y.-Z. Shi, W.-Q. Zhang, M. Cai, and J. Liu, “Variance regularization of RNNLM for speech recognition,” in Proc. ICASSP, 2014, pp. 4931-4935. doi: 10.1109/ICASSP.2014.6854532.
W.-W. Liu, W.-Q. Zhang, Y.-Z. Shi, A. Ji, J. Xu, and J. Liu, “Improved phonotactic language recognition based on RNN feature reconstruction,” in Proc. ICASSP, 2014, pp. 5359-5363. doi: 10.1109/ICASSP.2014.6854619.
W.-W. Liu, W.-Q. Zhang, and J. Liu, “Phonotactic language identification based on time-gap-weighted lattice kernels,” in Proc. Interspeech, 2014, pp. 3022-3026. doi: 10.21437/Interspeech.2014-606.
W.-L. Zhang, D. Qu, W.-Q. Zhang, and B.-C. Li, “Speaker adaptation based on sparse and low-rank eigenphone matrix estimation,” in Proc. Interspeech, 2014, pp. 2792-2796. doi: 10.21437/Interspeech.2014-496.
Z.-Y. Li, W.-Q. Zhang, W.-W. Liu, Y. Tian, and J. Liu, “Text-independent speaker verification via state alignment,” in Proc. Odyssey, 2014, pp. 68–72. doi: 10.21437/Odyssey.2014-10.
Y.-Z. Shi, W.-Q. Zhang, M. Cai, and J. Liu, “Temporal kernel neural network language model,” in Proc. ICASSP, 2013, pp. 8247-8251. doi: 10.1109/ICASSP.2013.6639273.
W.-Q. Zhang, Z.-Y. Li, W. Liu, and J. Liu, “THU-EE system fusion for the NIST 2012 speaker recognition evaluation,” in Proc. Interspeech, 2013, pp. 2474-2478. doi: 10.21437/Interspeech.2013-413.
W. Liu, W.-Q. Zhang, Zhang, Z.-Y. Li, and J. Liu. “Parallel absolute-relative feature based phonotactic language recognition,” in Proc. Interspeech, 2013, pp. 59-63. doi: 10.21437/Interspeech.2013-38.
W.-L. Zhang, W.-Q. Zhang, and B.-C. Li, “Compact acoustic modeling based on acoustic manifold using a mixture of factor analyzers,” in Proc. ASRU, 2013, pp. 37-42. doi: 10.1109/ASRU.2013.6707702.
Z.-Y. Li, W.-Q. Zhang, L. He, and J. Liu, “Complementary combination in i-vector level for language recognition,” in Proc. Odyssey, 2012, pp. 334-337. Available: https://www.isca-archive.org/odyssey_2012/li12_odyssey.html
Y.-Z. Shi, W.-Q. Zhang, and J. Liu, “Robust audio fingerprinting based on local spectral luminance maxima scheme,” in Proc. Interspeech, 2011, pp. 2485-2488. doi: 10.21437/Interspeech.2011-636.
W.-L. Zhang, W.-Q. Zhang, and B.-C. Li, “Speaker adaptation based on speaker-dependent eigenphone estimation,” in Proc. ASRU, 2011, pp. 48-52. doi: 10.1109/ASRU.2011.6163904.
W.-Q. Zhang, Y. Deng, L. He, and J. Liu, “Variant time-frequency cepstral features for speaker recognition,” in Proc. Interspeech, 2010, pp. 2122-2125. doi: 10.21437/Interspeech.2010-160.
S. Meng, W.-Q. Zhang, and J. Liu, “Combining Chinese spoken term detection systems via side-information conditioned linear logistic regression,” in Proc. Interspeech, 2010, pp. 685-688. doi: 10.21437/Interspeech.2010-260.
J. Yang, J. Liu, and W.-Q. Zhang, “A fast query by humming system based on notes,” in Proc. Interspeech, 2010, pp. 2898-2901. doi: 10.21437/Interspeech.2010-753.
W.-Q. Zhang, Y. Shan, and J. Liu, “Multiple background models for speaker verification,” in Proc. Odyssey, 2010, pp. 47-51. Available: https://www.isca-archive.org/odyssey_2010/zhang10_odyssey.html
W.-Q. Zhang and J. Liu, “Two-stage method for specific audio retrieval,” in Proc. ICASSP, 2007, pp. IV-85-88. doi: 10.1109/ICASSP.2007.367169.

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