Raphael Schumann

Raphael Schumann

Raphael Schumann, B.A.

Research assistant at the Statistical NLP Group under supervision of Prof. Dr. Stefan Riezler.

News

  • November: Will attend CoNLL 2019 in Hong Kong

Research Interests

  • Conversational AI
  • Sequence-to-Sequence
  • Text Summarization

Curriculum Vitae

Education

2019 (expected) Master of Arts, Computational Linguistics
Heidelberg University, Germany
2019 Visiting Graduate Researcher
University of Waterloo, Canada
2015 Bachelor of Arts, Computational Linguistics with Minor Computer Science
Heidelberg University, Germany

Employment

04/2018 - 10/2018 Research Intern
Nuance, Montréal, Canada
07/2017 - 10/2017 Research Intern
Bosch, Palo Alto, US
04/2017 - 06/2017 Research Intern
Nuance, Aachen, Germany
05/2016 - 03/2017 Research Assistant
Heidelberg Institute for Theoretical Studies, Germany
10/2015 - 04/2016 Machine Learning Intern
IBM, Böblingen, Germany

Talks

2019 Active Learning via Membership Query Synthesis for Semi-supervised Sentence Classification
CoNLL 2019, oral presentation, Hong Kong
2018 Transcription Errors in Context of Intent Detection and Slot Filling
Carnegie Mellon University, LTI Sphinx Lunch, Pittsburgh, US
M*Modal, Pittsburgh, US
2018 Incorporating ASR Errors with Attention-based, Jointly Trained RNN for Intent Detection and Slot Filling
ICASSP 2018, oral presentation, Calgary, Canada

Publications

  1. Raphael Schumann and Ines Rehbein
    Active Learning via Membership Query Synthesis for Semi-supervised Sentence Classification
    Conference on Computational Natural Language Learning (CoNLL), Hong Kong, 2019
    pdf | bib 
    @inproceedings{schumann2019,
  author = {Schumann, Raphael and Rehbein, Ines},
  title = {Active Learning via Membership Query Synthesis for Semi-supervised Sentence Classification},
  journal = {Conference on Computational Natural Language Learning},
  journal-abbrev = {CoNLL},
  year = {2019},
  city = {Hong Kong},
  url = {https://www.cl.uni-heidelberg.de/~rehbein/slides/MQS_conll2019.pdf}
}
  2. Raphael Schumann and Pongtep Angkititrakul
    Incorporating ASR Errors with Attention-based, Jointly RNN for Intent Detection and Slot Filling
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, Canada, 2018
    pdf | bib 
    @inproceedings{schumann2018,
  author = {Schumann, Raphael and Angkititrakul, Pongtep},
  title = {Incorporating ASR Errors with Attention-based, Jointly RNN for Intent Detection and Slot Filling},
  journal = {IEEE International Conference on Acoustics, Speech and Signal Processing},
  journal-abbrev = {ICASSP},
  year = {2018},
  city = {Calgary},
  country = {Canada},
  url = {https://ieeexplore.ieee.org/document/8461598}
}
  3. Marilisa Amoia, Frank Diehl, Jesus Gimenez, Joel Pinto, Raphael Schumann, Fabian Stemmer, Paul Vozila and Yi Zhang
    Scalable Wide and Deep Learning for Computer Assisted Coding
    Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Industry Track (NAACL-HLT), New Orleans, LA, USA, 2018
    pdf | bib 
    @inproceedings{amoia2018,
  author = {Amoia, Marilisa and Diehl, Frank and Gimenez, Jesus and Pinto, Joel and Schumann, Raphael and Stemmer, Fabian and Vozila, Paul and Zhang, Yi},
  title = {Scalable Wide and Deep Learning for Computer Assisted Coding},
  journal = {Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Industry Track},
  journal-abbrev = {NAACL-HLT},
  year = {2018},
  city = {New Orleans, LA},
  country = {USA},
  url = {https://www.aclweb.org/anthology/N18-3001.pdf}
}