Meng, Helen

Creation and Evaluation of a Pretertiary Artificial Intelligence (AI) Curriculum

Chiu, T. K. F., Meng, H., Chai, C.-S., King, I., Wong, S., & Yam, Y. (2022) · IEEE Transactions on Education

Artificial Intelligence in EducationTeaching and Learning Programming

Cited by 380

Replay and Synthetic Speech Detection with Res2Net Architecture

Li, X., Li, N., Weng, C., Liu, X., Su, D., Yu, D., & Meng, H. (2021) · ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech Recognition and SynthesisBiometric Identification and Security

Cited by 186

A phenomenographic approach on teacher conceptions of teaching Artificial Intelligence (AI) in K-12 schools

Yau, K. W., CHAI, C. S., Chiu, T. K. F., Meng, H., King, I., & Yam, Y. (2023) · Education and Information Technologies

Artificial Intelligence in EducationTeaching and Learning Programming

Cited by 160

Recent Progress in the CUHK Dysarthric Speech Recognition System

Liu, S., Geng, M., Hu, S., Xie, X., Cui, M., Yu, J., Liu, X., & Meng, H. (2021) · IEEE/ACM Transactions on Audio, Speech, and Language Processing

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 96

Critique-GRPO: Advancing LLM Reasoning with Natural Language and Numerical Feedback

Zhang, X., Zhang, Y., Sun, H., Feng, K., Lu, C., Yang, C., & Meng, H. (2025) · arXiv

Topic ModelingReinforcement Learning in Robotics

Cited by 92

Dilated Residual Network with Multi-head Self-attention for Speech Emotion Recognition

Li, R., Wu, Z., Jia, J., Zhao, S., & Meng, H. (2019) · ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Emotion and Mood RecognitionSpeech Recognition and Synthesis

Cited by 82

Learning Discriminative Features from Spectrograms Using Center Loss for Speech Emotion Recognition

Dai, D., Wu, Z., Li, R., Wu, X., Jia, J., & Meng, H. (2019) · ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Emotion and Mood RecognitionSpeech Recognition and Synthesis

Cited by 58

Speaker adaptation using spectro-temporal deep features for dysarthric and elderly speech recognition

Geng, M., Xie, X., Ye, Z., Wang, T., Li, G., Hu, S., Liu, X., & Meng, H. (2022) · IEEE/ACM Transactions on Audio Speech and Language Processing

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 48

Development of the CUHK Dysarthric Speech Recognition System for the UA Speech Corpus

Yu, J., Xie, X., Liu, S., Hu, S., Lam, M. W. Y., Wu, X., Wong, K. H., Liu, X., & Meng, H. (2018) · Interspeech 2018

Speech Recognition and SynthesisVoice and Speech Disorders

Cited by 47

Adversarial Data Augmentation for Disordered Speech Recognition

Jin, Z., Geng, M., Xie, X., Yu, J., Liu, S., Liu, X., & Meng, H. (2021) · Interspeech 2021

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 37

Exploiting Cross Domain Acoustic-to-Articulatory Inverted Features for Disordered Speech Recognition

Hu, S., Liu, S., Xie, X., Geng, M., Wang, T., Hu, S., Cui, M., Liu, X., & Meng, H. (2022) · ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 14

Neural Architecture Search for LF-MMI Trained Time Delay Neural Networks

Hu, S., Xie, X., Liu, S., Cui, M., Geng, M., Liu, X., & Meng, H. (2021) · ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech Recognition and SynthesisAdvanced Neural Network Applications

Cited by 6

MMSU: A Massive Multi-task Spoken Language Understanding and Reasoning Benchmark

Wang, D., Li, J., Wu, J., Yang, D., Chen, X., Zhang, T., & Meng, H. (2025) · arXiv

Speech Recognition and SynthesisSpeech and dialogue systems

Cited by 1