Institute

Studying

Research


 

Thang Vu

Full Professor (Carl-Zeiss-Stiftung Professor)
Ngoc Thang Vu

Ngoc Thang Vu
Phone +49 711 685-81372
Fax+49 711 685-81366
Room01.011
E-Mail
Address
University of Stuttgart
Institute for Natural Language Processing (NLP)
Pfaffenwaldring 5 b
70569 Stuttgart
Deutschland

Consultation

Thursdays 10 - 11 a.m.

You can find more details about my research group (Digital Phonetics) on this webpage.


Projects

1. Investigating the Interaction between Speech and Language Processing for Spoken Language Understanding: A Case Study for Sentiment Analysis (SFB 732 A8, 2016-2018) (Project website)

2. Multilingual Speech Recognition (Project with Sony, 2017- )

3. Intelligent Agents for Real Estate Consulting (Projekt with IIB, 2017-)
Teaching

SS 2018

1. Computational Linguistics Team Laboratory: Phonetics

2. Spoken Language Processing

3. Ethics and NLP

WS 2017/2018

1. Speech Recognition

2. Deep Learning for Speech and Language Processing

SS 2017

1. Computational Linguistics Team Laboratory: Phonetics

2. Dialog Modeling

3. Distributed Representation in NLP (only for CS Bsc)

WS 2016/2017

1. Speech Recognition

2. Deep Learning for Speech and Language Processing

3. Affective Computing and Emotion Analysis

4. Speech Synthesis

SS 2016

1. Computational Linguistics Team Laboratory: Phonetics (see C@MPUS)

WS 2015/2016

1. Speech Recognition (see LSF)

2. Deep Learning for Speech and Language Processing (see LSF)

 

Publications

2018

1. M. Blohm, G. Jagfeld, E. Sood, X. Yu and N.T. Vu. "Comparing Attention-based Convolutional and Recurrent Neural Networks: Success and Limitations in Machine Reading Comprehension". In Proceedings of the SIGNLL Conference on Computational Natural Language Learning (CoNLL), 2018.

2. C.Y Li and N.T. Vu. "Densely Connected Convolutional Networks for Speech Recognition". In Proceedings of the 13th ITG Conference on Speech Communication, 2018.

3. P. Denisov, N.T. Vu and M. Ferras. "Unsupervised Domain Adaptation by Adversarial Learning for Robust Speech Recognition". In Proceedings of the 13th ITG Conference on Speech Communication, 2018.

4. D. Grießhaber, N.T. Vu and J. Maucher. "Low-Resource Text Classification using Domain-Adversarial Learning". In Proceedings of the 6th International Conference on Statistical Language and Speech Processing, 2018.

5. S. Papay, S. Padó and N.T. Vu. "Addressing Low-Resource Scenarios with Character-aware Embeddings". In Proceedings of the Second Workshop on Subword and Character Level Models@ NAACL-HLT, 2018. 

6. S. Stehwien, N.T. Vu, A. Schweitzer. "Effects of Word Embeddings on Neural Network-based Pitch Accent Detection". In Proceedings of the 9th Speech Prosody Conference, 2018.

7. K.A. Nguyen, S. Schulte im Walde, N.T. Vu. "Introducing Two Vietnamese Datasets for Evaluating Semantic Models of (Dis-)Similarity and Relatedness". In Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), 2018.

8. M. Wand, N.T. Vu, J. Schmidhuber. "Investigations on End-to-end Audiovisual Fusion". In Proceedings of the 43rd EEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018.

9. M. Neumann, N.T. Vu. "Cross-lingual and Multilingual Speech Emotion Recognition on English and French". In Proceedings of the 43rd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018.

10. D. Ortega, N.T.Vu. "Lexico-acoustic Neural-based Models for Dialog Act Classification". In Proceedings of the 43rd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018.

2017

1. G. Jagfeld, N.T.Vu. "Encoding Word Confusion Networks with Recurrent Neural Networks for Dialog State Tracking". In Proceedings of the Speech-Centric Natural Language Processing Workshop @EMNLP, 2017.

2. M. Stiefel, N.T. Vu. "Enriching ASR Lattices with POS Tags for Dependency Parsing". In Proceedings of the Speech-Centric Natural Language Processing Workshop @EMNLP, 2017.

3. I. Roesiger, S. Stehwien, A. Riester, N.T. Vu. "Improving coreference resolution with automatically predicted prosodic information". In Proceedings of the Speech-Centric Natural Language Processing Workshop @EMNLP, 2017.

4. X. Yu, A. Faleńska, N.T. Vu. "A General-Purpose Tagger with Convolutional Neural Networks". In Proceedings of the Subword and Character Level Models in NLP Workshop @EMNLP, 2017.

5. K.A. Nguyen, M. Köper, S. Schulte im Walder, N.T. Vu. "Hierarchical Embeddings for Hypernymy Detection and Directionality". In Proceedings of EMNLP, 2017.

6. D. Ortega, N.T. Vu. "Neural-based Context Representation Learning for Dialog Act Classification". In Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue (SIGDIAL), 2017.

7. M. Neumann, N.T.Vu. "Attentive Convolutional Neural Network based Speech Emotion Recognition: A Study on the Impact of Input Features, Signal Length, and Acted Speech". In Proceedings of Interspeech, 2017.

8. S. Stehwien, N.T.Vu "Prosodic Event Recognition using Convolutional Neural Networks with Context Information". In Proceedings of Interspeech, 2017.

9. X. Yu, N.T.Vu. "Character Composition Model with Convolutional Neural Networks for Dependency Parsing on Morphologically Rich Languages". In Proceedings of ACL, 2017.

10. N.T. Vu. "Linguistics Meets Deep Learning: A Breakthrough Solution in Spoken Language Understanding?". Digital Phonetics Colloquium, Stuttgart, 2017.

11. K.A. Nguyen, S. Schulte im Walde, N.T. Vu. "Distinguishing Antonyms and Synonyms in a Pattern-based Neural Network". In Proceedings of EACL, 2017.

12. S. Stehwien, N.T. Vu. "First Step Towards Enhancing Word Embeddings with Pitch Accent Features for DNN-based Slot Filling on Recognized Text". In Proceedings of ESSV, 2017.

 

2016

1. K.A. Nguyen, S. Schulte im Walde, N.T. Vu. "Neural-based Noise Filtering from Word Embeddings". In Proceedings of COLING, 2016.

2. Ö. Çetinoğlu, S. Schulz and N.T. Vu, "Challenges of Computational Processing of Code-Switching". In Proceedings of 2nd Workshop on Computational Approaches to Linguistic Code Switching @EMNLP, 2016.

3. N.T. Vu, "Sequential Convolutional Neural Networks for Slot Filling in Spoken Language Understanding".  In Proceedings of Interspeech, 2016.

4. S. Stehwien, N.T. Vu, "Exploring the Correlation of Pitch Accents and Semantic Slots for Spoken Language Understanding". In Proceedings of Interspeech, 2016.

5. A. Schweitzer, N.T. Vu, "Cross-Gender and Cross-Dialect Tone Recognition for Vietnamese". In Proceedings of Interspeech, 2016.

6. D.T. Le, N.T. Vu, A. Blessing, "Towards a text analysis system for political debates". In Proceedings of the 10th Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities (LaTeCH) - in conjunction with ACL, 2016.

7. K.A. Nguyen, S. Schulte im Walde, N.T. Vu. "Integrating Distributional Lexical Contrast into Word Embeddings for Antonym-Synonym Distinction". In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL), 2016. [Outstanding paper]

8. N.T. Vu, H. Adel, P. Gupta and H. Schütze. "Combining Recurrent and Convolutional Neural Networks for Relation Classification". In Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), 2016.

9. N.T. Vu, P. Gupta, H. Adel and H. Schütze. "Bi-directional Recurrent Neural Network with Ranking Loss for Spoken Language Understanding". In Proceedings of the 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016.

Google Scholar

Services
  • 10/2015 - present                       Assistant Professor at IMS, University of Stuttgart
  • 10-2014 - 09/2015                      Visiting Professor at CIS, University of München
  • 04/2014 - 09/2015                      Senior Research Scientist, Nuance
  • 2014                                         Dr.-Ing. Computer Science, KIT
  • 2009                                         Diplom Computer Science, KIT
Supervision

I offer several BSc and MSc thesis topics related to automatic speech recognition, speech understanding and deep learning. Please come to my hour office or write me an email.