Qian Kun, M.Eng.

Technische Universität München

Institute of Human-Machine-Communication (Prof. Rigoll)

at the moment at the University Passau

Short Biography

Kun Qian received his master degree in signal and information processing from Nanjing University of Science and Technology (NUST) in P. R. China, 2014. Currently he is working on his Ph.D. degree in electrical engineering and information technology at Technical University of Munich (TUM), Germany. He was sponsored by scholarships to conduct cooperative research at Nanyang Technological University (NTU), Singapore, and Tokyo Institute of Technology (Tokyo Tech), Japan. His main research interests include: signal processing, machine learning, biomedical engineering, and deep learning with high performance computing system.

Publications

Refereed Journal Papers

2017

  • Kun Qian, Zixing Zhang, Alice Baird and Björn Schuller, "Active Learning for Bird Sound Classification via a Kernel-based Extreme Learning Machine", The Journal of the Acoustical Society of America, vol. 142, no. 4, pp. 1796-1804, 2017. (IF: 1.547)
  • Kun Qian, Christoph Janott, Vedhas Pandit, Zixing Zhang, Clemens Heiser, Winfried Hohenhorst, Michael Herzog, Werner Hemmert and Björn Schuller, "Classifi cation of the Excitation Location of Snore Sounds in the Upper Airway by Acoustic Multi-Feature Analysis", IEEE Transactions on Biomedical Engineering, vol. 64, no. 8, pp. 1731-1741, 2017. (IF: 3.577)
  • Kun Qian, Zixing Zhang, Alice Baird and Björn Schuller, "Active Learning for Bird Sounds Classi fication", Acta Acustica united with Acustica, vol. 103, no. 3, pp. 361-364, 2017. (IF: 1.119)
  • Jian Guo, Kun Qian, Gongxuan Zhang, Huijie Xu and Björn Schuller, "Accelerating biomedical signal processing using GPU: A case study of snore sounds feature extraction", Interdisciplinary Sciences: Computational Life Sciences, 2017, in press. (IF: 0.753)

2015

  • Kun Qian, Zhiyong Xu, Huijie Xu, Yaqi Wu and Zhao Zhao, "Automatic detection, segmentation and classi fication of snore related signals from overnight audio recording", IET Signal Processing, vol. 9, no. 1, pp. 21-29, 2015. (IF: 1.298)

2014

  • Kun Qian, Jian Guo, Huijie Xu, Zhaomeng Zhu and Gongxuan Zhang, "Snore related signals processing in a private cloud computing system", Interdisciplinary Sciences: Computational Life Sciences, vol. 6, no. 3, pp. 216-221, 2014. (IF: 0.753)
  • Yuzhuo Fang, Zhiyong Xu, Guang Cheng and Kun Qian, "Direction estimation of microphone array direct wave based on adaptive blind identi cation", Journal of Nanjing University of Science and Technology, vol. 38, no. 2, pp. 264-270, 2014.

2013

  • Kun Qian, Yuzhuo Fang, Zhiyong Xu and Huijie Xu, "Comparison of two acoustic features for classi fication of different snore signals", Chinese Journal of Electron Devices, vol. 36, no. 4, pp. 455-459, 2013.

Refereed Conference Papers

    2017

  • Kun Qian, Zhao Ren, Vedhas Pandit, Zijiang Yang, Zixing Zhang and BjörnSchuller, "Wavelets Revisited for the Classi fication of Acoustic Scenes", in Proceedings of the Workshop on Detection and Classi fication of Acoustic Scenes and Events (DCASE), in press, 2017.
  • Zhao Ren, Vedhas Pandit, Kun Qian, Zijiang Yang, Zixing Zhang and Björn Schuller, "Deep Sequential Image Features for Acoustic Scene Classi fication", in Proceedings of the Workshop on Detection and Classi cation of Acoustic Scenes and Events (DCASE), in press, 2017.
  • Kun Qian, Christoph Janott, Jun Deng, Clemens Heiser, Winfried Hohenhorst, Michael Herzog, Nicholas Cummins and Björn Schuller, "Snore Sound Recognition: On Wavelets and Classi ers from Deep Nets to Kernels", in Proceedings of the 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3737-3740, 2017.
  • Jun Deng, Nicholas Cummins, Maximilian Schmitt, Kun Qian, Fabien Ringeval and Björn Schuller, "Speech-based Diagnosis of Autism Spectrum Condition by Generative Adversarial Network Representations", in Proceedings of the ACM 7th Digital Health (DH), pp. 53-57, 2017.
  • Jian Guo, Kun Qian, Björn Schuller and Satoshi Matsuoka, "GPU-based Training of Autoencoders for Bird Sound Data Processing", in Proceedings of the IEEE International Conference on Consumer Electronics-Taiwan (ICCE-Taiwan), pp. 53-57, 2017.
  • Björn Schuller, Stefan Steidl, Anton Batliner, Elika Bergelson, Jarek Krajewski, Christoph Janott, Andrei Amatuni, Marisa Casillas, Amdanda Seidl, Melanie Soderstrom, S. Anne Warlaumont, Guillermo Hidalgo, Sebastian Schnieder, Clemens Heiser, Winfried Hohenhorst, Michael Herzog, Maximilian Schmitt, Kun Qian, Yue Zhang, George Trigeorgis, Panagiotis Tzirakis and Stefanos Zafeiriou, "The INTERSPEECH 2017 computational paralinguistics challenge: Addressee, Cold & Snoring", in Proceedings of INTERSPEECH, pp. 3442-3446, 2017.

        2016

      • Kun Qian, Christoph Janott, Zixing Zhang, Clemens Heiser and Björn Schuller, "Wavelet features for classi fication of vote snore sounds", in Proceedings of the 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 221-225, 2016.
      • Jian Guo, Kun Qian, Huijie Xu, Christoph Janott, Björn Schuller and Satoshi Matsuoka, "GPU-Based Fast Signal Processing for Large Amounts of Snore Sound Data", in Proceedings of the IEEE 5th Global Conference on Consumer Electronics (GCCE), pp. 523-524, 2016.
      • Maximilian Schmitt, Christoph Janott, Vedhas Pandit, Kun Qian, Clemens Heiser, Werner Hemmert and Björn Schuller, "A Bag-of-Audio-Words Approach for Snore Sounds Excitation Localisation", in Proceedings of the 12th ITG Conference on Speech Communication, pp. 230-234, 2016.

        2015

      • Kun Qian, Zixing Zhang, Fabien Ringeval and Björn Schuller, "Bird sounds classi fication by large scale acoustic features and extreme learning machine", in Proceedings of the 3rd IEEE Global Conference on Signal and Information Processing (GlobalSIP), pp. 1317-1321, 2015.

        2014

      • Kun Qian, Zhiyong Xu, Huijie Xu and Boon Poh Ng, "Automatic detection of inspiration related snoring signals from original audio recording", in Proceedings of the 2nd IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP), pp. 95-99, 2014.

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