Conference Papers

*: Corresponding Author, #: Co-First Author

2021

  1. Kun Qian*#, Tomoya Koike#, Kota Tamada, Toru Takumi, Björn W. Schuller, and Yoshiharu Yamamoto, “Sensing the Sounds of Silence: A Pilot Study on the Detection of Model Mice of Autism Spectrum Disorder from Ultrasonic Vocalisations”, in Proceedings of EMBC, accepted, in press, pp.1–4, Guadalajara, Mexico, October 2021.
  2. Tomoya Koike, Kun Qian*, Björn W. Schuller, and Yoshiharu Yamamoto, “STransferring Cross-Corpus Knowledge: An Investigation on Data Augmentation for Heart Sound Classification”, in Proceedings of EMBC, accepted, in press, pp.1–4, Guadalajara, Mexico, October 2021.
  3. Kun Qian*, Björn W. Schuller, and Yoshiharu Yamamoto, “Recent Advances in Computer Audition for Diagnosing COVID-19: An Overview”, in Proceedings of LifeTech, pp. 185-186, Nara, Japan, March 2021.
  4. Meishu Song, Kun Qian*, Bin Chen, Keiju Okabayashi, Emilia Parada-Cabaleiro, Zijiang Yang, Shuo Liu, Kazumasa Togami, Ichiro Hidaka, Yueheng Wang, Björn W. Schuller, and Yoshiharu Yamamoto, “Predicting Group Work Performance from Physical Handwriting Features in a Smart English Classroom”, in Proceedings of ICDSP, accepted, in press, pp. 1-5, Chengdu, China, February 2021.

2020

  1. Yu Qiao, Kun Qian*, and Ziping Zhao*, “Learning Higher Representations from Bioacoustics: A Sequence-to-Sequence Deep Learning Approach for Bird Sound Classification”, in Proceedings of ICONIP, pp. 130-138, Bangkok, Thailand, November 2020.
  2. Yu Qiao, Kun Qian*, Z. Zhao*, and X. Zhao, “Are You Speaking with a Mask? An Investigation on Attention based Deep Temporal Convolutional Neural Networks for Mask Detection Task”, in Proceedings of CSMT, 163-174, Best Paper Award, Taiyuan, China, November 2020.
  3. 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 Proceedings of INTERSPEECH, pp. 4946-4950, Shanghai, China, October 2020.
  4. 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 Proceedings of INTERSPEECH, pp. 2047-2051, Shanghai, China, October 2020.
  5. 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 Proceedings of EMBC, pp. 74-77, Montréal, Canada, July 2020.
  6. 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 LifeTech, pp. 366-367, Kyoto, Japan, March 2020.

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 ICECE, pp. 346-350, Xi’an, China, December 2019.
  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 ISPACS, pp. 1-2, Taipei, 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 CSMT, pp. 133-143, Harbin, China, December 2019.
  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 ISICDM, pp. 71-75, Best Paper Nomination Award, Xi’an, 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 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 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 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 ACM 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 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 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 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 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 ACM 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 ICCE-Taiwan, pp. 53-57, Best Paper Award Honorable Mention, Taipei, 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 ICASSP, pp. 221-225, Shanghai, 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 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 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 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 ICISCE, pp. 59-62, Shanghai, 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 ChinaSIP, pp. 95-99, Xi’an, 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 ICCSEE, pp. 984-987, Hangzhou, 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 APPT, 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 ITA, Chengdu, China, pp. 91-95, November 2013.