报告题目：(APSIPA Distinguished Lecturer Program)

Blind source separation based on unsupervisedand semi-supervisedlearningfor multichannel audio data

报 告 人：日本东京大学Hiroshi Saruwatari教授

报告时间：2019年11月15日 10：30

报告地点：航海学院西配楼215会议室

报告摘要：

Blind source separation (BSS) is an unsupervised learning approach for estimating original source signals using only mixed signals observed in        multichannel inputs. In particular, BSS algorithms based on independent component analysis (ICA) and independent vector analysis (IVA), in which the   independence among source signals is mainly used for the separation, have been studied actively in the past decade. In this lecture, looking back their      history from ICA to IVA, we focus our attention on the new extension to low-rank spectrogram modeling and sparse representation, and introduce            independent low-rank matrix analysis (ILRMA). In ILRMA, several source models based on complex heavy-tailed distributions are explained with the     discussion on fruitful relation between non-Gaussianity and low-rankness.Finally, thanks to audio big data capability, ILRMA and deep learning are combined, resulting in thesophisticatedhybrid method“independent deeply learned matrix analysis (IDLMA).”In addition to the theoretical basis of the algorithms, some applications combining BSS and real-world audio system will be reviewed, e.g., binaural hearing-aid system and distributed microphone array system for speech detection.

报告人简介：

Hiroshi Saruwatari received the B.E., M.E., and Ph.D. degrees from Nagoya University, Japan, in 1991, 1993, and 2000, respectively.He joined SECOM IS Laboratory, Japan, in 1993, and Nara Institute of Science and Technology, Japan, in 2000.He is currently a ProfessoratUniversity of Tokyo, Japan. His research interests include statistical speech signal processing, blind source separation (BSS), audio enhancement,androbot audition. He has successfully achieved hiscareer, especially on BSS researches including theoretical bridge between unsupervised         learning and spatial signal processing, and development ofcorrespondingreal-time algorithms.His research results were successful implementinto the world's first commercially available       Independent-Component-Analysis-based BSS microphone in 2007. He published 95refereedjournalspapers and 330 conference papers,which were citations morn than 6700times. He             received paper awards from IEICE in 2001 and 2006, from TAFin 2004, 2009 and 2012, from IEEE-IROS2005 in 2006, and from APSIPA in 2013and 2018. He received DOCOMO Mobile Science Award in 2011, Ichimura Award in 2013, The Commendation for Science and Technology by the Minister of Education in 2015, and Achievement Award from IEICE in 2017. He   won the first prize in IEEE MLSP2007 BSS Competition. He has beenan active volunteerfor IEEE, EURASIP, IEICE, and ASJ, including chair posts of international conferences and            associate editor of journals.