Forschung und wissenschaftliche Publikationen

(peer-reviewed)

  • P. Eickhoff, M. Möller, T. Pekarek Rosin, J. Twiefel, C. Weber, and S. Wermter, “Bring the noise: Introducing noise robustness to pretrained automatic speech recognition,” in Proceedings of the International Conference on Artificial Neural Networks (ICANN), (Crete, Greece), Springer, 2023 submitted.
  • H. Fang, N. Wittmer, J. Twiefel, S. Wermter, and Gerkmann, “Partially adaptive scheme for multichannel joint reduction of ego-noise and environmental noise,” in Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), (Rhodes Island, Greece), IEEE, 2023 accepted, to appear.
  • M. Möller, J. Twiefel, C. Weber, and S. Wermter, “Controlling the noise robustness of end-to-end automatic speech recognition systems,” in Proceedings of the International Joint Conference on Neural Networks (IJCNN 2021), (Virtual Event), 2021. PDF
  • J. Twiefel, Robust Bidirectional Processing for Speech-controlled Robotic Scenarios. PhD thesis, Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2020. PDF
  • X. Hinaut and J. Twiefel, “Teach your robot your language! trainable neural parser for modelling human sentence processing: Examples for 15 languages,” IEEE Transactions on Cognitive and Developmental Systems, vol. 12, pp. 179–188, 2019. PDF
  • L. Qu, C. Weber, E. Lakomkin, J. Twiefel, and S. Wermter, “Combining articulatory features with end-to-end learning in speech recognition,” in International Conference on Artificial Neural Networks, pp. 500–510, Springer, 2018. PDF
  • M. Tietz, T. Alpay, J. Twiefel, and S. Wermter, “Semi-supervised phoneme recognition with recurrent ladder networks,” in International Conference on Artificial Neural Networks (ICANN), (Alghero, Italy), pp. 3–10, Springer, 2017. PDF
  • J. Twiefel, X. Hinaut, and S. Wermter, “Syntactic reanalysis in language models for speech recognition,” in Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), (Lisbon, Portugal), pp. 215–220, IEEE, 2017. PDF
  • H. G. Ng, P. Anton, M. Brügger, N. Churamani, E. Fließwasser, T. Hummel, J. Mayer, W. Mustafa, T. L. C. Nguyen, Q. Nguyen, M. Soll, S. Springenberg, S. Griffiths, S. Heinrich, N. Navarro-Guerrero, E. Strahl, J. Twiefel, C. Weber, and S. Wermter, “Hey robot, why don’t you talk to me?,” in IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), (Lisbon, Portugal), pp. 728–731, IEEE, 2017.
  • N. Churamani, P. Anton, M. Brügger, E. Fließwasser, T. Hummel, J. Mayer, W. Mustafa, H. G. Ng, T. L. C. Nguyen, Q. Nguyen, M. Soll, S. Springenberg, S. Griffiths, S. Heinrich, N. Navarro-Guerrero, E. Strahl, J. Twiefel, C. Weber, and S. Wermter, “The impact of personalisation on human-robot interaction in learning scenarios,” in Fifth International Conference on Human Agent Interaction (HAI), (Bielefeld, Germany), pp. 171–180, ACM, 2017. PDF
  • F. Cruz, G. I. Parisi, J. Twiefel, and S. Wermter, “Multi-modal integration of dynamic audiovisual patterns for an interactive reinforcement learning scenario,” in IEEE International Conference on Intelligent Robots and Systems (IROS), (Daejeon, Korea), pp. 759–766, IEEE, 2016. PDF
  • X. Hinaut, J. Twiefel, and S. Wermter, “Recurrent neural network for syntax learning with flexible predicates for robotic architectures,” in Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), pp. 150–151, IEEE, 2016. PDF
  • I. Wieser, S. Toprak, A. Grenzing, T. Hinz, S. Auddy, E. C. Karaoguz, A. Chandran, M. Remmels, A. El Shinawi, K. Josifovski, L. Chennuru Vankadara, F. Ul Wahab, A. M. Bahnemiri, D. Sahu, S. Heinrich, N. Navarro-Guerrero, E. Strahl, J. Twiefel, and S. Wermter, “A robotic home assistant with memory aid functionality,” in IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), Video Session, (Ney York, USA), p. 369, IEEE, 2016.
  • I. Wieser, S. Toprak, A. Grenzing, T. Hinz, S. Auddy, E. C. Karaoğuz, A. Chandran, M. Remmels, A. El Shinawi, J. Josifovski, et al., “A robotic home assistant with memory aid functionality,” in Joint German/Austrian Conference on Artificial Intelligence (Künstliche Intelligenz), (Klagenfurt, Austria), pp. 102–115, Springer, 2016. PDF
  • J. Twiefel, X. Hinaut, and S. Wermter, “Semantic Role Labelling for Robot Instructions using Echo State Networks,” in European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), (Bruges,Belgium), pp. 695–700, Springer, 2016. PDF
  • X. Hinaut, J. Twiefel, M. Borghetti Soares, P. Barros, L. Mici, and S. Wermter, “Humanoidly speaking – learning about the world and language with a humanoid friendly robot,” in International Joint Conference on Artificial Intelligence (IJCAI), Video Competition, (Buenos Aires, Argentina), https://youtu.be/FpYDco3ZgkU, 2015.
  • J. Twiefel, X. Hinaut, M. Borghetti, E. Strahl, and S. Wermter, “Using natural language feedback in a neuro-inspired integrated multimodal robotic architecture,” in IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), (Ney York, USA), pp. 52–57, IEEE, 2016. PDF
  • F. Cruz, J. Twiefel, S. Magg, C. Weber, and S. Wermter, “Interactive Reinforcement Learning through Speech Guidance in a Domestic Scenario,” in International Joint Conference on Neural Networks (IJCNN), (Killarney, Ireland), pp. 1–8, 2015. PDF
  • X. Hinaut, J. Twiefel, M. Petit, P. Dominey, and S. Wermter, “A Recurrent Neural Network for Multiple Language Acquisition: Starting with English and French,” in Conference on Neural Information Processing Systems (NIPS), Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches, (Montréal, Canada), 2015. PDF
  • X. Hinaut and J. Twiefel, “Recurrent neural network sentence parser for multiple languages with flexible meaning representations for home scenarios,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Workshop on Bio-inspired Social Robot Learning in Home Scenarios, (Daejeon, Korea), 2016.
  • F. Cruz, J. Twiefel, and S. Wermter, “Performing a cleaning task in a simulated human-robot interaction environment,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Workshop An Open-source Recipe for Teaching/Learning Robotics with a Simulator, (Hamburg, Germany), IEEE, 2015.
  • J. Davila-Chacon, J. Twiefel, J. Liu, and S. Wermter, “Improving humanoid robot speech recognition with sound source localisation,” in Artificial Neural Networks and Machine Learning–ICANN 2014, pp. 619–626, Hamburg, Germany: Springer, 2014. PDF
  • J. Twiefel, T. Baumann, S. Heinrich, and S. Wermter, “Improving Domain-independent Cloud-based Speech Recognition with Domain-Dependent Phonetic Post-Processing.,” in Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI-14), (Québec City, Canada), pp. 1529–1536, 2014. PDF
  • S. Heinrich, P. Folleher, P. Springstübe, E. Strahl, J. Twiefel, C. Weber, and S. Wermter, “Object learning with natural language in a distributed intelligent system: A case study of human-robot interaction,” in Foundations and Practical Applications of Cognitive Systems and Information Processing, pp. 811–819, Chongqing, China: Springer, 2012. PDF