Ming-Hsiang Su received a PhD from the Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan. From 2013 to 2020, he conducted postdoctoral research in the Computer Science and Information Engineering Department at National Cheng Kung University in Tainan, Taiwan. Since 2020, he has been an assistant professor in the Department of Data Science at Soochow University in Taipei, Taiwan. His research interests encompass spoken dialogue systems, personality trait perception, speech emotion recognition, and speech signal processing.

Deep Learning, Natural Language Processing, Speech Signal Processing, Spoken Dialog system, Emotion and Personality Perception.

Job Title – Assistant Professor (August 2020 – )

Company Name - The Department of Data Science at Soochow University

No.70, Linhsi Road, Shihlin District, Taipei City 111, Taiwan.

Job Title – Postdoctoral Fellow (August 2013 – July 2020)

Company Name - The Department of Computer Science and Information Engineering (CSIE) at National Cheng Kung University

Location - No.1, University Road, Tainan City 701, Taiwan.

Job Title – Lecturer (June 2013 – July 2013)

Company Name – Skill Evaluation Center of Workforce Development Agency Minstry of Labor

Location - No. 501, Section 2, Límíng Rd, Nantun District, Taichung City, 408.

Job Title – Lecturer (February 2012 – January 2013)

Company Name – The Department of Management Information Systems at National Pingtung University of Science and Technology

Location - 1, Shuefu Road, Neipu, Pingtung 91201, Taiwan, R.O.C.

Job Title – Lecturer (September 2006 – January 2013)

Company Name – The Department of Mathematics at National Chung Cheng University

Location - 168, University Rd., Min-Hsiung, Chia-Yi 621 Taiwan, R.O.C.

Job Title – R & D Engineer (August 2003 – September 2004)

Company Name – Cino Group

Location – Taipei, Taiwan, R.O.C.

113   中國文學版本相似度比對及對話系統之建置 (113-2221-E-031 -002 -)

1. M.-H. Su and C.-H. Wu, “Chinese Spoken Dialog System,” Routledge Handbook of Chinese Discourse Analysis, pp. 500-518, 2019.

1. J.‑H. Wang, M.‑H. Su, Y.‑Z. Zeng, V. C.‑M. Chu, P. T. Le, T. Pham, X. Lu, Y.‑H. Li, and J.‑C. Wang, “Semantic-Based Public Opinion Analysis System,” Electronics, vol. 13, no. 11, 2024. (SCI, IF: 2.6)

2. J.-H. Wang, P. T. Le, F.-C. Jhou, M.-H. Su, K.-C. Li, S.-L. Chen, T. Pham, J.-L. He, C.-Y. Wang, J.-C. Wang, and P.-C. Chang, “Few-Shot Image Segmentation Using Generating Mask with Meta-Learning Classifier Weight Transformer Network,” Electronics, vol. 13, no. 13, 2024. (SCI, IF: 2.6)

3. J.-H. Wang, P. T. Le, W.-S. Bee, W. R. Putri, M.-H. Su, K.-C. Li, S.-L. Chen, J.-L. He, T. Pham, Y.-H. Li, and J.-C. Wang, “Implementation of Sound Direction Detection and Mixed Source Separation in Embedded Systems,” Sensors, vol. 24, no. 13, 4351, 2024. (SCI, IF: 3.4)

4. M.-H. Su, and C.-Y. Lee, “Establishment of an Automatic Crop Classification and Disease Detection System: Applied to Apple and Tomato Disease Detection,” Journal of Advanced Technology & Management, vol. 12, no. 2, pp. 50-69, 2024.

5. M.-H. Su; S.-W. Ho; S.-Y. Hsu; H.-Y. Lin, “Text-to-Motion Transformation: MotionGPT,” Journal of Advanced Technology & Management, vol. 12, no. 2, pp. 1-11, 2024.

6. M.-H. Su, C.-H. Wu, and C.-Y. Liao, “Conditional Adversarial Learning for Empathetic Dialogue Response Generation,” APSIPA Transactions on Signal and Information Processing, vol. 12, no. 1, 2023. 

7. J.-H. Hsu, M.-H. Su, C.-H. Wu, and Y.-H. Chen, “Speech Emotion Recognition Considering Nonverbal Vocalization in Affective Conversations,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, DOI: 10.1109/TASLP.2021.3076364, 2021. (SCI, IF:2.95)

8. M.-H. Su, C. H. Wu, and H. T. Cheng, ”A Two-Stage Transformer-Based Approach for Variable-Length Abstractive Summarization,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 28, pp. 2061-2072, 2020.

9. M.-H. Su, C.-H. Wu, and L.-Y. Chen, “Attention-based Response Generation Using Parallel Double Q-Learning for Dialog Policy Decision in a Conversational System,” IEEE Transactions on Audio, Speech and Language Processing, vol. 28, pp. 131-143, 2019. (SCI, IF:2.95)

10. M.-H. Su, C.-H. Wu, K.-Y. Huang, and T.-H. Yang, “Cell-Coupled Long Short-Term Memory With L-Skip Fusion Mechanism for Mood Disorder Detection Through Elicited Audiovisual Features,” IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2019.2899884, 2019. (SCI, IF:7.982)

11. Q.-B. Hong, C.-H. Wu, M.-H. Su, and C.-C. Chang, “Exploring Macroscopic and Microscopic Fluctuations of Elicited Facial Expressions for Mood Disorder Classification,” IEEE Transactions on Affective Computing, 2019. (SCI, IF:4.585)

12. K.-Y. Huang, C.-H. Wu, and M.-H. Su, “Attention-based Convolutional Neural Network and Long Short-term Memory for Short-term Detection of Mood Disorders based on Elicited Speech Responses,” Pattern Recognition, 88, 668-678, Elsevier, April 2019. (SCI, IF: 3.962)

13. M.-H. Su, C. -H. Wu, K.-Y. Huang, and W.-H. Lin, “Response Selection and Automatic Message-Response Expansion in Retrieval-Based QA Systems using Semantic Dependency Pair Model,” ACM Transactions on Asian and Low-Resource Language Information Processing, 18(1), 3:1-3:24, ACM, November 2018. (SCI)

14. K.-Y. Huang, C.-H. Wu, M.-H. Su, and Y.-T. Kuo, “Detecting Unipolar and Bipolar Depressive Disorders from Elicited Speech Responses Using Latent Affective Structure,” IEEE Transactions on Affective Computing, DOI:10.1109/TAFFC.2018.2803178, IEEE, February 2018. (SCI, IF:4.585)

15. C. -H. Wu, M. -H. Su, and W. -B. Liang, “Miscommunication handling in spoken dialog systems based on error-aware dialog state detection,” EURASIP Journal on Audio, Speech, and Music Processing, 1(9), 1-17, Springer, December 2017. (SCI, IF:3.057)

16. T.-H. Yang, C.-H. Wu, K.-Y. Huang, M.-H. Su, “Coupled HMM-based multimodal fusion for mood disorder detection through elicited audio-visual signals,” Journal of Ambient Intelligence and Humanized Computing, 8(6), 895-906, Springer, November 2017. (SCI, IF:1.423)

17. M.-H. Su, C.-H. Wu, and Y.-T. Zheng, “Exploiting Turn-Taking Temporal Evolution for Personality Trait Perception in Dyadic Conversations,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, 24(4), 733-744, IEEE, February 2016. (SCI, IF:2.95)

18. P.-T. Yu, B.-Y. Wang, and M.-H. Su, “Lecture capture with real time rearrangement of visual elements: ‐ impact on student performance,” Journal of Computer Assisted Learning, 31(6), 655-670, 2015. (SSCI, IF:1.859)

19. P.-T. Yu, Y.-H. Liao, M.-H. Su, “A Near-Reality Approach to Improve the e-Learning Open Courseware,” Journal of Educational Technology & Society, 16(4), 2013. (SSCI, IF:1.767)

20. C.-Y. Tsai, M.-H. Su, P.-T. Yu, “Based on the Concept of Learning Corner to Construct an Information TV System to Increase Student Learning Opportunities,” Journal of Convergence Information Technology, 8(8), 2013.

21. P.-Ta Yu, M.-H. Su, P.-J. Cheng, and Y.-H. Liao, “Applying Online Group Studies Environment to Enhance Student Reading Ability and Learning Effectiveness,” Journal of Internet Technology, 13(6), 981-988, 2012. (SCI, IF:1.301)

22. P.-T. Yu, Y.-H. Liao, M.-H. Su, P.-J. Cheng, and C.-H. Pai, “A Rapid Auto-Indexing Technology for Designing Readable e-Learning Content,” The International Review of Research in Open and Distance Learning, 13(5), pp. 20-38, 2012. (SSCI, IF:1.734) 

1. W.-T. Huang, Y.-C. Liu and M.-H. Su, “Application of Large Language Model-Based Prompt Engineering for Key Information Extraction from Audio-Visual Content,” in Proceeding of the 36th Conference on Computational Linguistics and Speech Processing (ROCLING 2024), Taipei, Taiwan, November 2024.

2. S.-H. Chen, W.-T. Huang, C.-H. Lai, Y.-L. Lin, and M.-H. Su, “Analysis and Discussion of Feature Extraction Technology for Musical Genre Classification,” in Proceeding of the 27th Conference of the Oriental COCOSDA (O-COCOSDA 2024), Hsinchu, Taiwan, October 2024.

3. Z.-J. Jian, and M.-H. Su, “Surface Defect Detection in Industrial Parts Using the YOLO-based Method with Enhanced Spatial Features and Attention Mechanism,” in Proceeding of 2024 16th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), IEEE, Takamatsu, Japan, July 2024.

4. J.-C. Hsu, and M.-H. Su, “Application of Skeleton Image Detection in Basketball Free Throw Posture Research,” in Proceeding of 2024 16th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), IEEE, Takamatsu, Japan, July 2024.

5. C.-Y. Lin, and M.-H. Su, “Model in Product Categorization,” in Proceeding of 2024 16th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), IEEE, Takamatsu, Japan, July 2024.

6. R.-C. Su, T.-E. Su, M.-H. Su, M. Pleva, and D. Hládek, “A Novel Named Entity Recognition Model Applied to Specialized Sequence Labeling,” in Proceeding of the 35th Conference on Computational Linguistics and Speech Processing (ROCLING 2023), Taipei, Taiwan, October 2023.

7. C.-W. Lee, D. Hládek, M. Pleva, Y.-F. Liao, and M.-H. Su, “Application of Wafer Defect Pattern Classification Model in the Semiconductor Industry,” in Proceeding of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Taipei, Taiwan, November 2023.

8. T.-F. Chen, Y.-X. Lin, M.-H. Su, P.-K. Chen, T.-C. Tai, J.-C. Wang, “Question Answering System Based on Pre-Training Model and Retrieval Reranking for Industry 4.0,” in Proceeding of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Taipei, Taiwan, November 2023.

9. Z.-J. He, and M.-H. Su, “Give Drivers a Safe Way Home: Early Warning of Car Accidents through Deep Learning,” in Proceeding of the International Conference on Consumer Electronics-Taiwan (ICCE-Taiwan), Ping-Tung, Taiwan, July 2023.

10. D. Hládek, J. Stas, M. Pleva, and M.-H. Su, “Comparison of Statistical Algorithms and Deep Learning for Slovak Document Classification,” in Proceeding of the International Conference on Consumer Electronics-Taiwan (ICCE-Taiwan), Taipei, Taiwan, July 2022.

11. T.-H. Yang, M. Pleva, D. Hládek, and M.-H. Su, “BERT-based Chinese Medicine Named Entity Recognition Model Applied to Medication Reminder Dialogue System,” In Proceeding of the 13th International Symposium on Chinese Spoken Language Processing (ISCSLP), Singapore, December 2022.

12. Y.-F. Liao, Y.-H. Huang, M. Pleva, D. Hládek, and M.-H. Su, “A Preliminary Study on Taiwanese OCR for Assisting Textual Database Construction from Historical Documents,” In Proceeding of the 13th International Symposium on Chinese Spoken Language Processing (ISCSLP), Singapore, December 2022.

13. M.-H. Su, C.-H. Wu, and Y. Chang, “Follow-Up Question Generation using Neural Tensor Network-based Domain Ontology Population in an Interview Coaching System,” Accepted for presentation in INTERSPEECH, Graz, Austria, ISCA, September 2019.

14. M.-H. Su, C.-H. Wu and P.-C. Shih, “Automatic Ontology Population Using Deep Learning for Triple Extraction,” Accepted for presentation in Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Lanzhou, China, November 2019.

15. Q.-B. Hong, C.-H. Wu, M.-H. Su and H.-M. Wang, “Sequential Speaker Embedding and Transfer Learning for Text-Independent Speaker Identification,” Accepted for presentation in Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Lanzhou, China, November 2019.

16. K.-Y. Huang, C.-H. Wu, Q.-B. Hong, M.-H. Su, and Y.-H. Chen, “Speech Emotion Recognition Using Deep Neural Network Considering Verbal and Nonverbal Speech Sounds,” in Proceeding of IEEE International Conference on Acoustics, Speech and Signal Processing, Brighton, United Kingdom, 5866-5870, IEEE, May 2019.

17. K.-Y. Huang, C.-H. Wu, Q.-B. Hong, M.-H. Su, and Y.-R. Zeng, “Speech Emotion Recognition using Convolutional Neural Network with Audio Word-based Embedding,” in Proceeding of the 11th International Symposium on Chinese Spoken Language Processing (ISCSLP), Taipei, Taiwan, November 2018.

18. M.-H. Su, C.-H. Wu, K.-Y. Huang, Q.-B. Hong, and H.-H. Huang, “Follow-up Question Generation using Pattern-based Seq2seq with a Small Corpus for Interview Coaching,” in Proceeding of INTERSPEECH, Hyderabad, India, 1006-1010, ISCA, September 2018.

19. M.-H. Su, C. H. Wu, K. Y. Huang, and Q. B. Hong, “LSTM-based Text Emotion Recognition Using Semantic and Emotional Word Vectors,” in Proceeding of 2018 First Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia), Beijing, China, IEEE, May 2018.

20. M.-H. Su, C.-H. Wu, K.-Y. Huang, and C.-K. Chen, “Attention-based Dialog State Tracking for Conversational Interview Coaching,” in Proceeding of IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, Alberta, Canada, 6144-6148, IEEE, April 2018.

21. K.-Y. Huang, C.-H. Wu, M.-H. Su, and C.-H. Chou, “Mood disorder identification using deep bottleneck features of elicited speech,” in Proceeding of Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Kuala Lumpur, Malaysia, 1648-1652, IEEE, December 2017.

22. M.-H. Su, C.-H. Wu, K.-Y. Huang, Q.-B. Hong, and H.-M. Wang, “Personality trait perception from speech signals using multiresolution analysis and convolutional neural networks,” in Proceeding of Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Kuala Lumpur, Malaysia, 1532-1536, IEEE, December 2017.

23. M.-H. Su, C.-H. Wu, K.-Y. Huang, Q.-B. Hong, and H.-M. Wang, “A Chatbot Using LSTM-based Multi-Layer Embedding for Elderly Care,” in Proceeding of International Conference on Orange Technologies, Singapore, 70-74, IEEE, December 2017.

24. M.-H. Su, C.-H. Wu, K.-Y. Huang, Q.-B. Hong, and H.-M. Wang, “Exploring Microscopic Fluctuation of Facial Expression for Mood Disorder Classification,” in Proceeding of International Conference on Orange Technology, Singapore, 65-69, IEEE, December 2017.

25. K.-Y. Huang, C.-H. Wu, M.-H. Su, and H.-C. Fu (2016, Dec). Mood Detection from Daily Conversational Speech Using Denoising Autoencoder and LSTM,” in Proceeding of International Conference on Acoustics, Speech and Signal Processing, New Orleans, LA, USA, 5125-5129, IEEE, March 2017.

26. M.-H. Su, C.-H. Wu, K.-Y. Huang, T.-H. Yang, and T.-C. Huang, “Dialog State Tracking for Interview Coaching Using Two-Level LSTM,” in Proceeding of the 10th International Symposium on Chinese Spoken Language Processing (ISCSLP), Tianjin, China, IEEE, October 2016

27. T.-H. Yang, C.-H. Wu, K.-Y. Huang, and M.-H. Su, “Detection of Mood Disorder Using Speech Emotion Profiles and LSTM,” in Proceeding of the 10th International Symposium on Chinese Spoken Language Processing (ISCSLP), Tianjin, China, IEEE, October 2016.

28. M.-H. Su, K.-Y. Huang, T.-H. Yang, K.-J. Lai and C.-H. Wu, “Dialog State Tracking and Dialog Action Detection Using Deep Learning Mechanism for Interview Coaching,” in Proceeding of the 20th International Conference on Asian Language Processing (IALP), Tainan, Taiwan, IEEE, November 2016.

29. M.-H. Su, W.-H. Lin, T.-H. Yang, and C.-H. Wu, “Automatic Text Segmentation from Unstructured Data Using LDA and Delta-BIC,” in Proceeding of the conference of 2015 National Computer Symposium, Pingtung, Taiwan, 2015.

30. M.-H. Su, Y.-T. Zheng, and C.-H. Wu, “Interlocutor Personality Perception based on BFI Profiles and Coupled HMMs in a Dyadic Conversation,” in Proceeding of the conference of International Symposium on Chinese Spoken Language Processing (ISCSLP), Singapore, IEEE, September 2014.