Conference Papers

2020

  1. Jing Han, Kun Qian*, Meishu Song, Zijiang Yang, Zhao Ren, Shuo Liu, Juan Liu, Huaiyuan Zheng, Wei Ji, Tomoya Koike, Xiao Li, Zixing Zhang, Yoshiharu Yamamoto, and Björn W. Schuller, “An Early Study on Intelligent Analysis of Speech under COVID-19: Severity, Sleep Quality, Fatigue, and Anxiety”, in the Proceeedings of INTERSPEECH, accepted, in press, pp. 1-5, October, 2020. (Corresponding Author)
  2. Tomoya Koike, Kun Qian*, Björn W. Schuller, and Yoshiharu Yamamoto, “Learning Higher Representations from pre-trained Deep Models with Data Augmentation for the ComParE 2020 Challenge Mask Task”, in the Proceeedings of INTERSPEECH, accepted, in press, pp. 1-5, October, 2020. (Corresponding Author)
  3. Tomoya Koike, Kun Qian*, Qiuqiang Kong, Mark D. Plumbley, Björn W. Schuller, and Yoshiharu Yamamoto, “Audio for Audio is Better? An Investigation on Transfer Learning Models for Heart Sound Classification”, in the Proceedings of 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 74-77, Montréal, Canada, July 2020. (Corresponding Author)
  4. Yueheng Wang, Kun Qian*, Jacob Nelson, Hiromichi Yagi, Akifumi Kishi, Kenji Morita, and Yoshiharu Yamamoto, “Can Affective Computing Better the Mental Status of the Electronic Games Player? A Perspective”, in Proceedings of the 2nd Global Conference on Life Sciences and Technologies (LifeTech), accepted, in press, pp. 366-367, Kyoto, Japan, March, 2020. (Corresponding Author)

2019

  1. Wei Guo, Xiang Zha, Kun Qian*, and Tao Chen, “Can Active Learning Benefit the Smart Grid? A Perspective on Overcoming the Data Scarcity”, in Proceedings of the 2nd International Conference on Electronics and Communication Engineering (ICECE), pp. 346-350, Xi’an, P. R. China, December 2019. (Corresponding Author)
  2. Kun Qian, Zhao Ren, Fengquan Dong, Wen-Hsing Lai, Björn W. Schuller, and Yoshiharu Yamamoto, “Deep Wavelets for Heart Sound Classification”, in Proceedings of the 28th International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), accepted, to appear, pp. 1-2, Taipei, Taiwan, China, December 2019.
  3. Zijiang Yang, Kun Qian*, Zhao Ren, Alice Baird, Zixing Zhang, and Björn W. Schuller, “Learning Multi-Resolution Representations for Acoustic Scene Classification via Neural Networks”, in Proceedings of the 7th China Conference on Sound and Music Technology (CSMT), pp. 133-143, Harbin, P.R. China, December 2019. (Corresponding Author)
  4. Kun Qian, Hiroyuki Kuromiya, Zhao Ren, Maximilian Schmitt, Zixing Zhang, Toru Nakamura, Kazuhiro Yoshiuchi, Björn W. Schuller, and Yoshiharu Yamamoto, “Automatic Detection of Major Depressive Disorder via a Bag-of-Behaviour-Words Approach”, in Proceedings of the 3rd International Symposium on Image Computing and Digital Medicine (ISICDM), pp. 71-75, Best Paper Nomination Award, Xi’an, P. R. China, August 2019.
  5. Kun Qian, Hiroyuki Kuromiya, Zixing Zhang, Jinhyuk Kim, Toru Nakamura, Kazuhiro Yoshiuchi, Björn W. Schuller, and Yoshiharu Yamamoto, “Teaching Machines to Know Your Depressive State: On Physical Activity in Health and Major Depressive Disorder”, in Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3592-3595, Berlin, Germany, July 2019.

2018

  1. Zhao Ren, Qiuqiang Kong, Kun Qian, Mark Plumbley and Björn W. Schuller, “Attention-based Convolutional Neural Networks for Acoustic Scene Classification”, in Proceedings of the Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE), pp. 39-43, Surrey, UK, November 2018.
  2. Zixing Zhang, Jing Han, Kun Qian and Björn W. Schuller, “Evolving Learning for Analysing Mood-Related Infant Vocalisation”, in Proceedings of INTERSPEECH, pp. 142-146, Hyderabad, India, September 2018.
  3. Björn W. Schuller, Stefan Steidl, Anton Batliner, Peter Marschik, Harald Baumeister, Fengquan Dong, Simone Hantke, Florian Pokorny, Eva-Maria Rathner, Katrin Bartl-Pokorny, Christa Einspieler, Dajie Zhang, Alice Baird, Shahin Amiriparian, Kun Qian, Zhao Ren, Maximilian Schmitt, Panagiotis Tzirakis and Stefanos Zafeiriou, “The INTERSPEECH 2018 Computational Paralinguistics Challenge: Atypical & Self-assessed Affect, Crying & Heart Beats”, in Proceedings of INTERSPEECH, pp. 122-126, Hyderabad, India, September 2018.
  4. Shahin Amiriparian, Maximilian Schmitt, Nicholas Cummins, Kun Qian, Fengquan Dong and Björn W. Schuller, “Deep Unsupervised Representation Learning for Abnormal Heart Sound Classification”, in Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 4776-4779, Honolulu, HI, USA, July 2018.
  5. Zhao Ren, Nicholas Cummins, Vedhas Pandit, Jing Han, Kun Qian and Björn W. Schuller, “Learning Imagebased Representations for Heart Sound Classification”, in Proceedings of the 8th ACM Digital Health (DH), pp. 143-147, Lyon, France, April 2018.

2017

  1. Kun Qian, Zhao Ren, Vedhas Pandit, Zijiang Yang, Zixing Zhang and Björn W. Schuller, “Wavelets Revisited for the Classication of Acoustic Scenes”, in Proceedings of the Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE), pp. 108-112, Munich, Germany, November 2017.
  2. Zhao Ren, Vedhas Pandit, Kun Qian, Zijiang Yang, Zixing Zhang and Björn W. Schuller, “Deep Sequential Image Features for Acoustic Scene Classification”, in Proceedings of the Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE), pp. 113-117, Munich, Germany, November 2017.
  3. Tao Chen, Kun Qian, Antti Mutanen, Björn W. Schuller, Pertti Järventausta and Wencong Su, “Classification of Electricity Customer Groups Towards Individualized Price Scheme Design”, in Proceedings of the North American Power Symposium (NAPS), pp. 1-4, Morgantown, WV, USA, September 2017.
  4. Björn W. 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, Stockholm, Sweden, August 2017.
  5. Kun Qian, Christoph Janott, Jun Deng, Clemens Heiser, Winfried Hohenhorst, Michael Herzog, Nicholas Cummins and Björn W. Schuller, “Snore Sound Recognition: On Wavelets and Classiers 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, Jeju Island, Korea, July 2017.
  6. Jun Deng, Nicholas Cummins, Maximilian Schmitt, Kun Qian, Fabien Ringeval and Björn W. 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, London, UK, July 2017.
  7. Jian Guo, Kun Qian, Björn W. 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, Best Paper Award Honorable Mention, Taipei, Taiwan, China, June 2017.

2016

  1. Kun Qian, Christoph Janott, Zixing Zhang, Clemens Heiser and Björn W. Schuller, “Wavelet Features for Classification of VOTE Snore Sounds”, in Proceedings of the 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 221-225, Shanghai, P. R. China, March 2016.
  2. Jian Guo, Kun Qian, Huijie Xu, Christoph Janott, Björn W. 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, Kyoto, Japan, October 2016.
  3. Maximilian Schmitt, Christoph Janott, Vedhas Pandit, Kun Qian, Clemens Heiser, Werner Hemmert and Björn W. Schuller, “A Bag-of Audio-Words Approach for Snore Sounds Excitation Localisation”, in Proceedings of the 12th ITG Conference on Speech Communication (ITG), pp. 230-234, Paderborn, Germany, October 2016.

2015

  1. Kun Qian, Zixing Zhang, Fabien Ringeval and Björn W. Schuller, “Bird Sounds Classication 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, Orlando, FL, USA, December 2015.
  2. Jian Guo, Kun Qian, Dongxu Han and Gongxuan Zhang, “A Private Cloud Instances Placement Algorithm based on Maximal Flow Algorithm”, in Proceedings of the 2nd International Conference on Information Science and Control Engineering (ICISCE), pp. 59-62, Shanghai, P. R. China, April 2015.

2014

  1. 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, Xi’an, P. R. China, July 2014.

2013

  1. Kun Qian, Yuzhuo Fang, Zhiyong Xu and Huijie Xu, “All Night Analysis of Snoring Signals by Formant Features”, in Proceedings of the International Conference on Computer Science and Electronics Engineering (ICCSEE), pp. 984-987, Hangzhou, P. R. China, March 2013.
  2. Jian Guo, Kun Qian, Zhaomeng Zhu, Gongxuan Zhang and Huijie Xu, “A Cloud Computing System for Snore Signals Processing”, in Proceedings of the International Workshop on Advanced Parallel Processing Technologies, pp. 359-366, Stockholm, Sweden, August 2013.
  3. Yaqi Wu, Zhao Zhao, Kun Qian, Zhiyong Xu and Huijie Xu, “Analysis of Long Duration Snore Related Signals based on Formant Features”, in Proceedings of the International Conference on Information Technology and Applications (ITA), Chengdu, P. R. China, pp. 91-95, November 2013.