Junior Professorship Computational Linguistics

Welcome to the chair of Junior Professorship Computational Linguistics at IMS Stuttgart. The group has been headed by Junior-Prof. Ngoc Thang Vu since October 2015.

We conduct research on the three following research areas:

  1. Methods for Speech Understanding:
    1. Automatic Speech Recognition
    2. Interface between Speech Recognition and Natural Language Understanding
    3. Representation Learning for Words, Phrases and Utterances
  2. Signals Encoded in Speech and their Roles for Understanding:
    1. Prosody
    2. Emotion
  3. Applications:
    1. Neural-based Dialog Systems
    2. Spoken Dialog Summarization



PhD Students:


  • Mahbub Ul Alam

MSc Students:

  • Mahbub Ul Alam
  • Bhavani Bhaskar
  • Matthias Blohm
  • Chia-Yu Li
  • Fangzhou Li
  • Jingwen Lou
  • Monique Marquez
  • Natalia Skaczkowska
  • Tanzia Haque Tanzi
  • Gisela Vallejo

BSc Students:

  • Jannik Frisch
  • Zoltán Czesnak




SS 2017

1. Computational Linguistics Team Laboratoy: Phonetics

2. Dialog Modeling

3. Distributed Representation in NLP (only 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)

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-)


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

2. 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.

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

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

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

6. 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.

7. 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.


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

Sybille Laderer
Telefon +49 (0) 711/685-81363
Fax+49 (0) 711/685-81366
Universität Stuttgart
Institut für Maschinelle Sprachverarbeitung
Pfaffenwaldring 5b
70569 Stuttgart