Daichi Kitamura
Personal Data
Place of Birth:
Date of Birth:
Address:
E-Mail:Website:Kagawa, Japan
March 11th, 1990
355 Chokushi, Takamatsu, Kagawa 761–8058, Japankitamura-d@t.kagawa-nct.ac.jp
http://d-kitamura.net

Educational BackgroundMar. 2017
Mar. 2014
Mar. 2012
Mar. 2010

Ph.D. degree in Informatics, School of Multidisciplinary Sciences, Department of Informatics,
SOKENDAI (The Graduate University for Advanced Studies), Japan
M.S. degree in Engineering, Graduate school of Information Science,
Nara Institute of Science and Technology (NAIST), Japan
B.S. degree in Engineering, Advanced Course in Industrial and Systems Engineering,
National Institute of Technology (NIT), Kagawa Collage, JapanFoundation degree of Engineering, Department of Electrical and Computer Engineering,
National Institute of Technology (NIT), Kagawa Collage, Japan

Research & Work Experiences
Jan. 2022–Present

Senior Lecturer of Department of Electrical and Computer Engineering, National Institute of Technology, Kagawa College, Japan

Apr. 2021–Present

Visitor of Nippon Telegraph and Telephone Corporation Communication Science Laboratories, Japan

Apr. 2018–Dec. 2021

Assistant Professor of Department of Electrical and Computer Engineering, National Institute of Technology, Kagawa College, Japan

Apr. 2018–Mar. 2020

Visiting Researcher of Department of Information Physics and Computing, Graduate School of Information Science and Technology, The University of Tokyo,
Japan

Apr. 2017–Mar. 2018

Project Research Associate of Department of Information Physics and Computing,
Graduate School of Information Science and Technology, The University ofTokyo, Japan

Apr. 2017–Sep. 2017

Part-Time Lecturer of Department of Human Environment Design, Faculty of
Human Life Design, Toyo University, Japan

Apr. 2014–Mar. 2017

Research Fellow (DC1) of Japan Society of the Promotion of Science (JSPS), JapanMay 2015–Feb. 2017

Research Assistant with Superordinate Wages of Research Organization of Information and Systems (ROIS), JapanMay 2014–Apr. 2015

Research Assistant of Research Organization of Information and Systems (ROIS),
Japan

Jun. 2013–Aug. 2013

Teaching Assistant of Graduate school of Information Science, Nara Instituteof Science and Technology (NAIST), Japan1

Volunteer Works
Jun. 2021–Present

Committee Member of Technical Group on Signal Processing, The Institute ofElectronics, Information and Communication Engineers (IEICE), Japan

Jun. 2018–Present

Committee Member of Technical Group on Engineering Acoustics, The Instituteof Electronics, Information and Communication Engineers (IEICE), Japan

Jul. 2017–Sep. 2018

Organizing Committee Member (Local Arrangement Chair) of 16th International
Workshop on Acoustic Signal Enhancement (IWAENC 2018), Japan

Mar. 2014–Mar. 2019Students and Young Researchers Forum Member of The Acoustical Society of Japan(ASJ), Japan

Jan. 2016–Feb. 2017

Evaluation Organizing Committee Member of Sixth Community-Based Signal Separation Evaluation Campaign (SiSEC 2016)

Sep. 2014–Sep. 2015

Evaluation Organizing Committee Member of Fifth Community-Based Signal Separation Evaluation Campaign (SiSEC 2015)

Awards Recieved
Dec. 2021
Jun. 2021
Dec. 2019Nov. 2018
Mar. 2018
Mar. 2018
Nov. 2017
Sep. 2017
Jul. 2017
Mar. 2017
Mar. 2016
Nov. 2015
Sep. 2015
Mar. 2015
Nov. 2014
May. 2014
Mar. 2014
Mar. 2014
Nov. 2013
Mar. 2010
Mar. 2010

Sadaoki Furui Prize Paper Award 2021, Asia-Paciﬁc Signal and Information Processing
Association (APSIPA)
Best Presentation Award, Information Processing Society of Japan 2021 Otogaku Symposium
2019 Young Author Best Paper Award, IEEE Signal Processing Society (SPS)Best Paper Award, Asia-Paciﬁc Signal and Information Processing Association (APSIPA)
Annual Summit and Conference 2018
The Telecom System Technology Award (Encouragement Award), The Telecommunication Advancement Foundation (TAF)
The 13th Itakura Prize Innovative Young Researcher Award, The Acoustical Society ofJapan (ASJ)
Best Paper Award, IEEE Signal Processing Society (SPS) Japan
FY2016 22nd Nagakura Research Incentive Award, SOKENDAI (The Graduate University for
Advanced Studies)
21st Annual Best of Computing Notable Books and Articles in Computing of 2016, ACM
Computing Reviews
Seventh (FY2016) Ikushi Prize, Japan Society for the Promotion of Science (JSPS)The Telecom System Technology Student Award, The Telecommunication Advancement
Foundation (TAF)
Student Conference Paper Award, IEEE Signal Processing Society (SPS) Japan Chapter
2015 The 1st Best Student Award, National Institute of Informatics (NII)The 37th Awaya Prize Young Researcher Award, The Acoustical Society of Japan (ASJ)
2013 Technical Group on Signal Processing Young Researcher’s Award, The Institute ofElectronics, Information and Communication Engineers (IEICE)
Total Exemption from Repayment of Scholarship Loan for Students with Outstanding Results, Japan Student Services Organization (JASSO)
Master’s Best Student Award, Nara Institute of Science and Technology (NAIST)NCSP’14 Student Paper Award, 2014 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP 2014)
The 8th Student Presentation Award, The Acoustical Society of Japan (ASJ)
The Best Graduation Research Award, Department of Electrical & Computer Engineering, Takamatsu National College of Technology (TNCT)Engineers Encouragement Award, The Shikoku section of the Institute of Electronics,
Information and Communication Engineers (IEICE)

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Competitive Funds
Apr. 2022–Mar. 2026

Apr. 2022–Mar. 2025

Apr. 2021–Mar. 2022

Apr. 2019–Mar. 2022

Apr. 2019–Mar. 2023

Aug. 2017–Mar. 2019

Jun. 2015
May 2014–Mar. 2017

Apr. 2013

JSPS Grant-in-Aid for Scientiﬁc Research (B) (KAKENHI), ”Mathematical Deepening of Audio Source Separation Based on Independence and Amplitude/Phase Modeling and Development of Multimodal Hearing-Aid system (Grant No. 22H03652)”, Principal Investigator,
Japan Society for the Promotion of Science (JSPS)
JSPS Grant-in-Aid for Scientiﬁc Research (B) (KAKENHI), ”Fundamental Study of Continuous
Blood Pressure Measurement Using a Wearable Sensor Attached to Nail Surface (Grant
No. 22H03982)”, Co-Investigator, Japan Society for the Promotion of Science (JSPS)”Analysis of Relative Characteristics for Multiple Musical Instruments Based on Matrix
Decomposition Theory and Deep Learning”, Principal Investigator, Ono Charitable Trust
for Acoustics
JSPS Grant-in-Aid for Young Scientists (KAKENHI), ”Uniﬁcation of Deep Learning and Generalized Mathematical Model for Independence-Based Audio Source Separation (Grant
No. 19K20306)”, Principal Investigator, Japan Society for the Promotion of Science (JSPS)
JSPS Grant-in-Aid for Scientiﬁc Research (A) (KAKENHI), ”Audio Augmented Reality andExtension of Audio Communication Ability Based on Small Data Machine Learning Theory(Grant No. 19H01116)”, Co-Investigator, Japan Society for the Promotion of Science (JSPS)
JSPS Grant-in-Aid for Research Activity start-up (KAKENHI), ”Extended Theories of Audio
Source Separation Based on Statistical Independence and Various Mathematical Structures(Grant No. 17H06572)”, Principal Investigator, Japan Society for the Promotion of Science(JSPS)
Grants for Researchers Attending International Conferences, The Telecommunications
Advanvement Foundation (TAF)
Grant-in-Aid for JSPS Fellows (DC1), ”Multi-Dimensional Media Processing Based on
Sparse Signal Decompositions and Its Application to Audio Augmented Reality (Grant
No. 14J10796)”, Principal Invectigator, Japan Society of the Promotion of Science (JSPS)
Grants for Researchers Attending International Conferences, NEC C&C Foundation

Research Interests
Field• Statistical Signal Processing,• Machine Learning• Pattern Recognition• Audio Signal Processing• Array Signal Processing• Optimization Theory

Topics• Blind and Supervised Audio Source Separation• Nonnegative Matrix Factorization• Independent Component Analysis• Deep Neural Networks

Publications
Book Chapters
1. Daichi Kitamura, Nobutaka Ono, Hiroshi Sawada, Hirokazu Kameoka, and Hiroshi Saruwatari, “Determined blind source separation with independent low-rank matrix analysis,” Audio Source Separation.
Signals and Communication Technology., Shoji Makino, Ed. Springer, Cham, pp. 125–155, March 2018.
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2. Daichi Kitamura, “Q11 What is beamforming?,” Acousticpedia for Beginners, Acoustical Society of Japan,
Eds. Corona Publishing, pp. 44–47, March 2017 (in Japanese).

Journal Papers
1. Shoya Kawaguchi and Daichi Kitamura, “Amplitude spectrogram prediction from mel-frequency cepstrum coeﬃcients using deep neural networks,” Journal of Signal Processing, vol. 27, no. 6, pp. 207–211,
November 2023.
2. Takuya Hasumi, Tomohiko Nakamura, Norihiro Takamune, Hiroshi Saruwatari, Daichi Kitamura, Yu
Takahashi, and Kazunobu Kondo, “PoP-IDLMA: Product-of-prior independent deeply learned matrix
analysis for multichannel music source separation,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 31, pp. 2680–2694, July 2023.
3. Yuto Kondo, Yuki Kubo, Norihiro Takamune, Daichi Kitamura, and Hiroshi Saruwatari, “Deﬁcientbasis-complementary rank-constrained spatial covariance matrix estimation based on multivariate
generalized Gaussian distribution for blind speech extraction,” EURASIP Journal on Advances in Signal
Processing, vol. 2022, no. 88, 24 pages, September 2022.
4. Yuta Iwase and Daichi Kitamura, “Supervised audio source separation based on nonnegative matrix
factorization with cosine similarity penalty,” IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E105-A, no. 6, pp. 906–913, Jun 2022.
5. Keigo Kamo, Yoshiki Mitsui, Yuki Kubo, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari,
Yu Takahashi, and Kazunobu Kondo, “Joint-diagonalizability-constrained multichannel nonnegative
matrix factorization based on time-variant multivariate complex sub-Gaussian distribution,” Signal
Processing, vol. 188, 108183, November 2021.
6. Fuga Oshima, Masaki Nakano, and Daichi Kitamura, “Interactive speech source separation based on
independent low-rank matrix analysis,” Acoustical Science and Technology, vol. 42, no. 4, pp. 222–225,
July 2021.
7. Kohei Yatabe and Daichi Kitamura, “Determined BSS based on time-frequency masking and its application to harmonic vector analysis,” IEEE/ACM Transaction on Audio, Speech, and Language Processing,vol. 29, pp. 1609–1625, April 2021.
8. Akihito Aiba, Minoru Yoshida, Daichi Kitamura, Shinnosuke Takamichi, and Hiroshi Saruwatari, “Noise
robust acoustic anomaly detection system with nonnegative matrix factorization based on generalized
Gaussian distribution,” IEICE Transactions on Information and Systems, vol. E104-D, no. 3, pp. 441–449,
March 2021.
9. Naoki Makishima, Yoshiki Mitsui, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi, and Kazunobu Kondo, “Independent deeply learned matrix analysis with automatic selectionof stable microphone-wise update and fast sourcewise update of demixing matrix,” Signal Processing,vol. 178, 107753, January 2021.
10. Daichi Kitamuraa and Kohei Yatabe, “Consistent independent low-rank matrix analysis for determinedblind source separation,” EURASIP Journal on Advances in Signal Processing, vol. 2020, no. 46, p. 35,
November 2020.
11. Yuki Kubo, Norihiro Takamune, Daichi Kitamura, and Hiroshi Saruwatari, “Blind speech extraction
based on rank-constrained spatial covariance matrix estimation with multivariate generalized Gaussian distribution,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 28, pp. 1948–
1963, June 2020.
12. Shinnosuke Takamichi, Yuki Saito, Norihiro Takamune, Daichi Kitamura, and Hiroshi Saruwatari,“Phase reconstruction from amplitude spectrograms based on directional-statistics deep neural networks,” Signal Processing, vol. 169, 107368, April 2020.
13. Shinichi Mogami, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi, Kazunobu
Kondo, and Nobutaka Ono, “Independent low-rank matrix analysis based on time-variant sub-Gaussian
source model for determined blind source separation,” IEEE/ACM Transactions on Audio, Speech, andLanguage Processing, vol. 28, pp. 503–518, December 2019.
14. Yuki Mitsufuji, Stefan Uhlich, Norihiro Takamune, Daichi Kitamuraa, Shoichi Koyama, and Hiroshi
Saruwatari, “Multichannel non-negative matrix factorization using banded spatial covariance matrices

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in wavenumber domain,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 28,
pp.49–60, October 2019.
15. Naoki Makishima, Shinichi Mogami, Norihiro Takamune, Daichi Kitamura, Hayato Sumino, Shinnosuke Takamichi, Hiroshi Saruwatari, and Nobutaka Ono, “Independent deeply learned matrix analysis
for determined audio source separation,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 27, no. 10, pp. 1601–1615, October 2019.
16. Hiroaki Nakajima, Daichi Kitamura, Norihiro Takamune, Hiroshi Saruwatari, and Nobutaka Ono,
“Bilevel optimization using stationary point of lower-level objective function for discriminative basis
learning in nonnegative matrix factorization,” IEEE Signal Processing Letters, vol. 26, no. 6, pp. 818–822,
June 2019.
17. Hiroshi Sawada, Nobutaka Ono, Hirokazu Kameoka, Daichi Kitamura, and Hiroshi Saruwatari, “A
review of blind source separation methods: Two converging routes to ILRMA originating from ICA
and NMF,” APSIPA Transactions on Signal and Information Processing, vol. 8, no. e12, pp. 1–14, May 2019.
18. Shinichi Mogami, Yoshiki Mitsui, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi, Kazunobu Kondo, Hiroaki Nakajima, and Hirokazu Kameoka, “Independent low-rank matrix
analysis based on generalized Kullback-Leibler divergence,” IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E102-A, no. 2, pp. 458–463, February 2019.
19. Daichi Kitamura, Shinichi Mogami, Yoshiki Mitsui, Norihiro Takamune, Hiroshi Saruwatari, Nobutaka
Ono, Yu Takahashi, and Kazunobu Kondo, “Generalized independent low-rank matrix analysis using
heavy-tailed distributions for blind source separation,” EURASIP Journal on Advances in Signal Processing,vol. 2018, no. 1, p. 28, May, 2018.
20. Yoshiaki Bando, Hiroshi Saruwatari, Nobutaka Ono, Shoji Makino, Katustoshi Itoyama, Daichi Kitamura,
Masaru Ishimura, Moe Takakusaki, Narumi Mae, Kouei Yamaoka, Yutaro Matsui, Yuichi Ambe, Masashi
Konyo, Satoshi Tadokoro, Kazuyoshi Yoshii, and Hiroshi G. Okuno, “Low-latency and high-quality
two-stage human-voice-enhancement system for a hose-shaped rescue robot,” Journal of Robotics andMechatronics, vol. 29, no. 1, pp.198–212, February 2017.
21. Daichi Kitamura, Nobutaka Ono, Hiroshi Sawada, Hirokazu Kameoka, and Hiroshi Saruwatari, “Determined blind source separation unifying independent vector analysis and nonnegative matrix factorization,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 24, no. 9, pp. 1626–1641,
September, 2016.
22. Daichi Kitamura, Hiroshi Saruwatari, Hirokazu Kameoka, Yu Takahashi, Kazunobu Kondo, and Satoshi
Nakamura, “Multichannel signal separation combining directional clustering and nonnegative matrix
factorization with spectrogram restoration,” IEEE/ACM Transactions on Audio, Speech, and Language
Processing, vol. 23, no. 4, pp. 654–669, April 2015.
23. Tomo Miyauchi, Daichi Kitamura, Hiroshi Saruwatari, and Satoshi Nakamura, “Depth estimation ofsound images using directional clustering and activation-shared nonnegative matrix factorization,”
Journal of Signal Processing, vol. 18, no. 4, pp. 217–220, July 2014 (corresponding author).
24. Daichi Kitamura, Hiroshi Saruwatari, Kosuke Yagi, Kiyohiro Shikano, Yu Takahashi, and Kazunobu
Kondo, “Music signal separation based on supervised nonnegative matrix factorization with orthogonality and maximum-divergence penalties,” IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E97-A, no. 5, pp. 1113–1118, May 2014.
25. Masahiro Harazono, Daichi Kitamura, and Masashi Nakayama, “Humbucking pickup response excitedby string vibration,” Acoustical Science and Technology, vol. 33, no. 5, pp. 301–309, 2012.

Peer-Reviewed International Conference Proceedings
1. Sota Misawa, Norihiro Takamune, Kohei Yatabe, Daichi Kitamura, and Hiroshi Saruwatari, “Blindsource separation using independent low-rank matrix analysis with spectrogram-consistency regularization,” Proceedings of Asia-Paciﬁc Signal and Information Processing Association Annual Summit andConference (APSIPA ASC 2023), Taipei, Taiwan, November 2023.
2. Koki Nishida, Norihiro Takamune, Rintaro Ikeshita, Daichi Kitamura, Hiroshi Saruwatari, and Tomohiro Nakatani, ”NoisyILRMA: Diffuse-noise-aware independent low-rank matrix analysis for fast blind5source extraction,” Proceedings of European Signal Processing Conference (EUSIPCO 2023), pp. 925–
929, Helsinki, Finland, September 2023.
3. Shoya Kawaguchi and Daichi Kitamura, “Amplitude spectrogram prediction from mel-frequency cepstrum coeﬃcients and loudness using deep neural networks,” Proceedings of RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP 2023), pp. 225–228, Hawaii,
USA, March 2023.
4. Fumiya Hasuike, Daichi Kitamura, and Rui Watanabe, “DNN-based frequency-domain permutation
solver for multichannel audio source separation,” Proceedings of Asia-Paciﬁc Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2022), pp. 872–877, Chiang Mai, Thailand,
November 2022.
5. Keito Murata, Daichi Kitamura, Daichi Ueki, and Ryo Saito, “Heart rate estimation of car driver using
radar sensors and blind source separation,” Proceedings of Asia-Paciﬁc Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2022), pp. 1157–1164, Chiang Mai, Thailand,
November 2022.
6. Masaya Kawamura, Tomohiko Nakamura, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi, andKazunobu Kondo, “Differentialble digital signal processing mixture model for synthesis parameter
extraction from mixture of harmonic sounds,” Proceedings of IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2022), pp. 941–945, Singapore, May 2022.
7. Yusaku Mizobuchi, Daichi Kitamura, Tomohiko Nakamura, Hiroshi Saruwatari, Yu Takahashi, andKazunobu Kondo, “Prior distribution design for music bleeding-sound reduction based on nonnegative
matrix factorization,” Proceedings of Asia-Paciﬁc Signal and Information Processing Association Annual
Summit and Conference (APSIPA ASC 2021), pp. 651–658, Tokyo, Japan, December 2021.
8. Takuya Hasumi, Tomohiko Nakamura, Norihiro Takamune, Hiroshi Saruwatari, Daichi Kitamura, Yu
Takahashi, and Kazunobu Kondo, “Multichannel audio source separation with independent deeply
learned matrix analysis using product of source models,” Proceedings of Asia-Paciﬁc Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2021), pp. 1226–1233, Tokyo, Japan,
December 2021.
9. Sota Misawa, Norihiro Takamune, Tomohiko Nakamura, Daichi Kitamura, Hiroshi Saruwatari, Masakazu
Une, and Shoji Makino, “Speech enhancement by noise self-supervised rank-constrained spatial covariance matrix estimation via independent deeply learned matrix analysis,” Proceedings of Asia-Paciﬁc Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2021), pp. 578–584,
Tokyo, Japan, December 2021.
10. Takuya Hasumi, Tomohiko Nakamura, Norihiro Takamune, Hiroshi Saruwatari, Daichi Kitamura, Yu
Takahashi, and Kazunobu Kondo, “Empirical Bayesian independent deeply learned matrix analysis for
multichannel audio source separation,” Proceedings of European Signal Processing Conference (EUSIPCO
2021), pp. 331–335, Dublin, Ireland, August 2021.
11. Naoki Narisawa, Rintaro Ikeshita, Norihiro Takamune, Daichi Kitamura, Tomohiko Nakamura, Hiroshi
Saruwatari, and Tomohiro Nakatani, “Independent deeply learned tensor analysis for determined audio source separation,” Proceedings of European Signal Processing Conference (EUSIPCO 2021), pp. 326–330,
Dublin, Ireland, August 2021.
12. Soichiro Oyabu, Daichi Kitamura, and Kohei Yatabe, “Linear multichannel blind source separation
based on time-frequency mask obtained by harmonic/percussive sound separation,” Proceedings of IEEE
International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021), pp. 201–205, Toronto,
Canada, June 2021.
13. Yuto Kondo, Yuki Kubo, Norihiro Takamune, Daichi Kitamura, and Hiroshi Saruwatari, “Deﬁcientbasis estimation of noise spatial covariance matrix for rank-constrained spatial covariance matrix
estimation method in blind speech extraction,” Proceedings of IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2021), pp. 806–810, Toronto, Canada, June 2021.
14. Rui Watanabe, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi, and Kazunobu Kondo, “DNN-basedfrequency component prediction for frequency-domain audio source separation,” Proceedings of European Signal Processing Conference (EUSIPCO 2020), pp. 805–809, Amsterdam, Netherlands, January
2021.

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15. Keigo Kamo, Yuki Kubo, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi, andKazunobu Kondo, “Joint-diagonalizability-constrained multichannel nonnegative matrix factorization
based on multivariate complex sub-Gaussian distribution,” Proceedings of European Signal Processing
Conference (EUSIPCO 2020), pp. 890–894, Amsterdam, Netherlands, January 2021.
16. Shuhei Yamaji and Daichi Kitamura, “DNN-based permutation solver for frequency-domain independent component analysis in two-source mixture case,” Proceedings of Asia-Paciﬁc Signal and Information
Processing Association Annual Summit and Conference (APSIPA ASC 2020), pp. 781–787, Auckland, New
Zealand, December 2020.
17. Keigo Kamo, Yuki Kubo, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi, andKazunobu Kondo, “Joint-diagonalizability-constrained multichannel nonnegative matrix factorization
based on multivariate complex Student’s t-distribution,” Proceedings of Asia-Paciﬁc Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2020), pp. 869–874, Auckland,
New Zealand, December 2020.
18. Masakazu Une, Yuki Kubo, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, and Shoji Makino,“Multichannel hearing-aid system based on basis-shared semi-supervised independent low-rank matrix analysis,” Proceedings of Forum Acusticum, pp. 811–817, Lyon, France, December 2020.
19. Keigo Kamo, Yuki Kubo, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi,
and Kazunobu Kondo, “Regularized fast multichannel nonnegative matrix factorization with ILRMAbased prior distribution of joint-diagonalization process,” Proceedings of IEEE International Conferenceon Acoustics, Speech and Signal Processing (ICASSP 2020), pp. 606–610, Barcelona, Spain, May 2020.
20. Tatsuki Kondo, Kanta Fukushige, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, Rintaro
Ikeshita, and Tomohiro Nakatani, “Convergence-guaranteed independent positive semideﬁnite tensor
analysis based on Student’s t distribution,” Proceedings of IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2020), pp. 681–685, Barcelona, Spain, May 2020.
21. Naoki Makishima, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi, and Kazunobu
Kondo, “Robust demixing ﬁlter update algorithm based on microphone-wise coordinate descent for independent deeply learned matrix analysis,” Proceedings of Asia-Paciﬁc Signal and Information Processing
Association Annual Summit and Conference (APSIPA ASC 2019), pp. 1868–1873, Lanzhou, China, November
2019.
22. Yuki Kubo, Norihiro Takamune, Daichi Kitamura, and Hiroshi Saruwatari, “Acceleration of rankconstrained spatial covariance matrix estimation for blind speech extraction,” Proceedings of AsiaPaciﬁc Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2019),
pp. 332–338, Lanzhou, China, November 2019.
23. Masakazu Une, Yuki Kubo, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, and Shoji Makino,“Evaluation of multichannel hearing aid system using rank-constrained spatial covariance matrix estimation,” Proceedings of Asia-Paciﬁc Signal and Information Processing Association Annual Summit andConference (APSIPA ASC 2019), pp. 1874–1879, Lanzhou, China, November 2019.
24. Naoki Makishima, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi, and Kazunobu
Kondo, “Column-wise update algorithm for independent deeply learned matrix analysis,” Proceedingsof International Congress on Acoustics (ICA 2019), pp. 2805–2812, Aachen, Germany, September 2019.
25. Yuki Kubo, Norihiro Takamune, Daichi Kitamura, and Hiroshi Saruwatari, “Eﬃcient full-rank spatial
covariance estimation using independent low-rank matrix analysis for blind source separation,” Proceedings of European Signal Processing Conference (EUSIPCO 2019), A Coruna, Spain, September 2019.
26. Naoki Makishima, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi, Kazunobu
Kondo, and Hiroaki Nakajima, “Generalized-Gaussian-distribution-based independent deeply learned
matrix analysis for multichannel audio source separation,” Proceedings of International Congress andExhibition on Noise Control Engineering (INTERNOISE 2019), Madrid, Spain, June 2019.
27. Kohei Yatabe and Daichi Kitamura, “Time-frequency-masking-based determined BSS with application
to sparse IVA,” Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing(ICASSP 2019), pp. 715–719, Brighton, U.K., May 2019.
28. Shinichi Mogami, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi, Kazunobu
Kondo, Hiroaki Nakajima, and Nobutaka Ono, “Independent low-rank matrix analysis based on time-7

variant sub-Gaussian source model,” Proceedings of Asia-Paciﬁc Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2018), pp. 1684–1691, November 2018.
29. Masakazu Une, Yuki Saito, Shinnosuke Takamichi, Daichi Kitamura, Ryoichi Miyazaki, and Hiroshi
Saruwatari, “Generative approach using the noise generation models for DNN-based speech synthesis
trained from noisy speech,” Proceedings of Asia-Paciﬁc Signal and Information Processing Association
Annual Summit and Conference (APSIPA ASC 2018), pp. 340–344, November 2018.
30. Shinnosuke Takamichi, Yuki Saito, Norihiro Takamune, Daichi Kitamura, and Hiroshi Saruwatari,“Phase reconstruction from amplitude spectrograms based on von-Mises-distribution deep neuralnetwork,” Proceedings of International Workshop on Acoustic Signal Enhancement (IWAENC 2018), pp.
286–290, Tokyo, Japan, September 2018.
31. Shinichi Mogami, Hayato Sumino, Daichi Kitamura, Norihiro Takamune, Shinnosuke Takamichi, Hiroshi Saruwatari, and Nobutaka Ono, “Independent deeply learned matrix analysis for multichannel
audio source separation,” Proceedings of European Signal Processing Conference (EUSIPCO 2018), pp. 1571–
1575, Roma, Italy, September, 2018.
32. Kohei Yatabe and Daichi Kitamura, “Determined blind source separation via proximal splitting algorithm,” Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP
2018), pp. 776–780, Calgary, Canada, April, 2018.
33. Yoshiki Mitsui, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi, and Kazunobu
Kondo, “Vectorwise coordinate descent algorithm for spatially regularized independent low-rank matrix analysis,” Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing(ICASSP 2018), pp. 746–750, Calgary, Canada, April, 2018.
34. Narumi Mae, Koei Yamaoka, Yoshiki Mitsui, Mitsuo Matsumoto, Shoji Makino, Daichi Kitamura, Nobutaka Ono, Takeshi Yamada, and Hiroshi Saruwatari, “Ego noise reduction and sound localization
adapted to human ears using hose-shaped rescue robot,” Proceedings of RISP International Workshop on
Nonlinear Circuits, Communications and Signal Processing (NCSP 2018), pp. 371–374, Hawaii, USA, March2018.
35. Moe Takakusaki, Daichi Kitamura, Nobutaka Ono, Shoji Makino, Takeshi Yamada, and Hiroshi Saruwatari,“Ego-noise reduction for hose-shaped rescue robot using basis-shared semi-supervised independent
low-rank matrix analysis,” Proceedings of RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP 2018), pp. 351–354, Hawaii, USA, March 2018 (Student Paper Award).
36. Narumi Mae, Yoshiki Mitsui, Shoji Makino, Daichi Kitamura, Nobutaka Ono, Takeshi Yamada, andHiroshi Saruwatari, ”Sound source localization using binaural different for hose-shaped rescue robot,”
Proceedings of Asia-Paciﬁc Signal and Information Processing Association Annual Summit and Conference(APSIPA ASC 2017), Kuala Lumpur, Malaysia, December, 2017.
37. Yoshiki Mitsui, Daichi Kitamura, Norihiro Takamune, Hiroshi Saruwatari, Yu Takahashi, and Kazunobu
Kondo, “Independent low-rank matrix analysis based on parametric majorization-equalization algorithm,” Proceedings of IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive
Processing (CAMSAP 2017), pp. 98–102, Curaçao, Dutch Antilles, December, 2017.
38. Sinichi Mogami, Daichi Kitamura, Yoshiki Mitsui, Norihiro Takamune, Hiroshi Saruwatari, and Nobutaka Ono, “Independent low-rank matrix analysis based on complex Student’s t-distribution for blindaudio source separation,” Proceedings of IEEE International Workshop on Machine Learning for Signal
Processing (MLSP 2017), Tokyo, Japan, September, 2017.
39. Daichi Kitamura, Nobutaka Ono, and Hiroshi Saruwatari, “Experimental analysis of optimal window
length for independent low-rank matrix analysis,” Proceedings of The 2017 European Signal Processing
Conference (EUSIPCO 2017), pp. 1210–1214, Kos, Greece, August 2017 (Invited Special Session).
40. Yoshiki Mitsui, Daichi Kitamura, Shinnosuke Takamichi, Nobutaka Ono, and Hiroshi Saruwatari, “Blindsource separation based on independent low-rank matrix analysis with sparse regularization for timeseries activity,” Proceedings of The 42nd IEEE International Conference on Acoustics, Speech and Signal
Processing (ICASSP 2017), pp. 21–25, New Orleans, U.S.A., March, 2017 (Student Paper Contest Finalist).
41. Antoine Liutkus, Fabian-Robert Stöter, Zafar Raﬁi, Daichi Kitamura, Bertrand Rivet, Nobutaka Ito,
Nobutaka Ono, and Julie Fontecave, “The 2016 signal separation evaluation campaign,” Proceedings of8

13th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2017), pp. 323–332,
Grenoble, France, February, 2017.
42. Narumi Mae, Masaru Ishimura, Daichi Kitamura, Nobutaka Ono, Takeshi Yamada, Shoji Makino, andHiroshi Saruwatari, “Ego noise reduction for hose-shaped rescue robot combining independent lowrank matrix analysis and multichannel noise cancellation,” Proceedings of 13th International Conferenceon Latent Variable Analysis and Signal Separation (LVA/ICA 2017), pp. 141–151, Grenoble, France, February,
2017.
43. Narumi Mae, Daichi Kitamura, Masaru Ishimura, Takeshi Yamada, and Shoji Makino, “Ego noise reduction for hose-shaped rescue robot combining independent low-rank matrix analysis and noise
cancellation,” Proceedings of Asia-Paciﬁc Signal and Information Process Processing Association Annual
Summit and Conference (APSIPA ASC 2016), Jeju, Korea, December 2016.
44. Hiroaki Nakajima, Daichi Kitamura, Norihiro Takamune, Shoichi Koyama, Hiroshi Saruwatari, Yu
Takahashi, and Kazunobu Kondo, “Audio signal separation using supervised NMF with time-variant
all-pole-model-based basis deformation,” Proceedings of Asia-Paciﬁc Signal and Information Process Processing Association Annual Summit and Conference (APSIPA ASC 2016), Jeju, Korea, December 2016.
45. Daichi Kitamura and Nobutaka Ono, “Eﬃcient initialization for nonnegative matrix factorization
based on nonnegative independent component analysis,” Proceedings of The 15th International Workshop
on Acoustic Signal Enhancement (IWAENC 2016), Xi’an, China, September 2016 (Student Paper Competition Finalist).
46. Daichi Kitamura, Nobutaka Ono, Hiroshi Saruwatari, Yu Takahashi, and Kazunobu Kondo, “Discriminative and reconstructive basis training for audio source separation with semi-supervised nonnegative
matrix factorization,” Proceedings of The 15th International Workshop on Acoustic Signal Enhancement(IWAENC 2016), Xi’an, China, September 2016.
47. Moe Takakusaki, Daichi Kitamura, Nobutaka Ono, Takeshi Yamada, Shoji Makino, and Hiroshi Saruwatari,“Ego-noise reduction for a hose-shaped rescue robot using determined rank-1 multichannel nonnegative matrix factorization,” Proceedings of The 15th International Workshop on Acoustic Signal Enhancement(IWAENC 2016), Xi’an, China, September 2016.
48. Hiroaki Nakajima, Daichi Kitamura, Norihiro Takamune, Shoichi Koyama, Hiroshi Saruwatari, Nobutaka Ono, Yu Takahashi, and Kazunobu Kondo, “Music signal separation using supervised NMF with
all-pole-model-based discriminative basis deformation,” Proceedings of The 2016 European Signal Processing Conference (EUSIPCO 2016), pp. 1143–1147, Budapest, Hungary, September 2016.
49. Daichi Kitamura, Nobutaka Ono, Hiroshi Sawada, Hirokazu Kameoka, and Hiroshi Saruwatari, “Relaxation of rank-1 spatial constraint in overdetermined blind source separation,” Proceedings of The
2015 European Signal Processing Conference (EUSIPCO 2015), pp. 1271–1275, Nice, France, September 2015
(Invited Special Session).
50. Nobutaka Ono, Zafar Raﬁi, Daichi Kitamura, Nobutaka Ito, and Antoine Liutkus, “The 2015 signal
separation evaluation campaign,” Proceedings of 12th International Conference on Latent Variable Analysis
and Signal Separation (LVA/ICA 2015), Liberec, Czech, August 2015.
51. Daichi Kitamura, Nobutaka Ono, Hiroshi Sawada, Hirokazu Kameoka, and Hiroshi Saruwatari, “Efﬁcient multichannel nonnegative matrix factorization exploiting rank-1 spatial model,” Proceedingsof IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2015), pp. 276–280,
Brisbane, Australia, April 2015.
52. Yuki Murota, Daichi Kitamura, Shoichi Koyama, Hiroshi Saruwatari, Satoshi Nakamura, “Statisticalmodeling of binaural signal and its application to binaural source separation,” Proceedings of IEEE
International Conference on Acoustics, Speech and Signal Processing (ICASSP 2015), pp. 494–498, Brisbane,
Australia, April 2015.
53. Daichi Kitamura, Hiroshi Saruwatari, Satoshi Nakamura, Yu Takahashi, Kazunobu Kondo, and Hirokazu Kameoka, “Hybrid multichannel signal separation using supervised nonnegative matrix factorization with spectrogram restoration,” Proceedings of Asia-Paciﬁc Signal and Information Processing
Association Annual Summit and Conference 2014 (APSIPA 2014), Siem Reap, Cambodia, December 2014
(Invited Special Session).

954. Daichi Kitamura, Hiroshi Saruwatari, Satoshi Nakamura, Yu Takahashi, Kazunobu Kondo, and Hirokazu Kameoka, “Divergence optimization in nonnegative matrix factorization with spectrogram
restoration for multichannel signal separation,” Proceedings of 4th Joint Workshop on Hands-free SpeechCommunication and Microphone Arrays (HSCMA 2014), pp. 92–96, Nancy, France, May 2014.
55. Yuki Murota, Daichi Kitamura, Hiroshi Saruwatari, Satoshi Nakamura, Yu Takahashi, and Kazunobu
Kondo, “Music signal separation based on Bayesian spectral amplitude estimator with automatic target
prior adaptation,” Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing(ICASSP 2014), pp. 7540–7544, Frolence, Italy, May 2014.
56. Daichi Kitamura, Hiroshi Saruwatari, Satoshi Nakamura, Yu Takahashi, Kazunobu Kondo, and Hirokazu Kameoka, “Online divergence switching for superresolution-based nonnegative matrix factorization,” Proceedings of 2014 RISP International Workshop on Nonlinear Circuits, Communications andSignal Processing (NCSP 2014), pp. 485–488, Hawaii, USA, March 2014 (Student Paper Award).
57. Tomo Miyauchi, Daichi Kitamura, Hiroshi Saruwatari, and Satoshi Nakamura, “Depth estimation ofsound images using directional clustering and activation-shared nonnegative matrix factorization,”
Proceedings of 2014 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP 2014), pp. 437–440, Hawaii, USA, March 2014 (Student Paper Award).
58. Daichi Kitamura, Hiroshi Saruwatari, Kosuke Yagi, Kiyohiro Shikano, Yu Takahashi, and Kazunobu
Kondo, “Robust music signal separation based on supervised nonnegative matrix factorization withprevention of basis sharing,” Proceedings of IEEE International Symposium on Signal Processing and Information Technology (ISSPIT 2013), pp. 392–397, Athens, Greece, December 2013.
59. Daichi Kitamura, Hiroshi Saruwatari, Kiyohiro Shikano, Kazunobu Kondo, and Yu Takahashi, “Musicsignal separation by supervised nonnegative matrix factorization with basis deformation,” Proceedingsof IEEE 18th International Conference on Digital Signal Processing (DSP 2013), Santorini, Greece, July 2013.
60. Daichi Kitamura, Hiroshi Saruwatari, Yusuke Iwao, Kiyohiro Shikano, Kazunobu Kondo, and Yu Takahashi, “Superresolution-based stereo signal separation via supervised nonnegative matrix factorization,” Proceedings of IEEE 18th International Conference on Digital Signal Processing (DSP 2013), Santorini,
Greece, July 2013.
61. Daichi Kitamura, Hiroshi Saruwatari, Kiyohiro Shikano, Kazunobu Kondo, and Yu Takahashi, “Regularized superresolution-based binaural signal separation with nonnegative matrix factorization,” Proceedings of 5th International Conference on 3D Systems and Applications (3DSA 2013), Osaka, Japan, June
2013.

Patents
1. Daichi Kitamura, Toshiki Tada, Kotaro Ogawa, Minako Terao, Kazuma Takenaka, “ELECTRONIC APPARATUS AND ITS CONTROL METHOD,” Japanese Unexamined Patent, Application No. 2021-120969(submitted on July 21st, 2021), and Publication No. JP 2023-016563 (published on February 2nd, 2023).
2. Daichi Kitamura, Hiroshi Saruwatari, Yuki Kubo, and Norihiro Takamune, “ACOUSTIC ANALYSIS DEVICE, ACOUSTIC ANALYSIS METHOD, AND ACOUSTIC ANALYSIS PROGRAM,” Application No. 17/782,546(submitted on December 1st, 2020), and Publication No. US-2023/0018030 A1 (published on January
19th, 2023).
3. Daichi Kitamura and Rui Watanabe, “AUDIO PROCESSING METHOD, METHOD FOR TRAINING ESTIMATION MODEL, AND AUDIO PROCESSING SYSTEM,” Application No. 17/896,671 (submitted on August
26th, 2022), and Publication No. US-2022/0406325 A1 (published on December 22nd, 2022).
4. Daichi Kitamura and Rui Watanabe, “SOUND PROCESSING METHODS AND APPARATUS,” Japanese Unexamined Patent, Application No. 2020-33347 (submitted on February 28th, 2020), and Publication No.
JP 2021-135446A (published on September 13th, 2021).
5. Daichi Kitamura, Yuki Kubo, Hiroshi Saruwatari, and Norihiro Takamune, “ACOUSTIC ANALYSIS APPARATUS, ACOUSTIC ANALYSIS METHOD, AND ACOUSTIC ANALYSIS PROGRAM,” Japanese Unexamined
Patent, Application No. 2019-220584 (submitted on December 5th, 2019), and Publication No. JP 202189388A (published on June 10th, 2021).

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6. Daichi Kitamura, Hiroaki Nakajima, Hiroshi Saruwatari, Nobutaka Ono, Yu Takahashi, Kazunobu
Kondo, “SIGNAL PROCESSING METHOD AND SOUND SIGNAL PROCESSOR,” Japanese Unexamined Patent,
Application No. 2016-032489 (submitted on February 23rd, 2016) and Publication No. JP 2017-151228A(published on August 31st, 2017)..
7. Daichi Kitamura, Hiroshi Saruwatari, and Yu Takahashi, “SOUND PROCESSING DEVICE,” Japanese Unexamined Patent, Application No. 2013-094475 (submitted on April 26th, 2013), and Publication No.
2014-215544 (published on November 17th, 2014).
8. Daichi Kitamura, Hiroshi Saruwatari, and Yu Takahashi, “ACOUSTIC ANALYZER,” Japanese Unexamined
Patent, Application No. 2013-004375 (submitted on January 15th, 2013), and Publication No. 2014-137389(published on July 28th, 2014).

Miscellaneous Works
1. Daichi Kitamura, “Audio source separation based on spectral and spatial models,” Tours University,
Invited Lecture, October 6th, 2023.
2. Daichi Kitamura, “Blind audio source separation based on time-frequency structure models,” Invited
Overview Session in Asia-Paciﬁc Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2021), Tokyo, Japan, December 2021.
3. Daichi Kitamura, “The BEEtles! Let it “BEE” performed by four bees,” MATLAB EXPO 2021 Japan Lightning
Talk, June 10th, 2021.
4. Hiroshi Sawada, Nobutaka Ono, Hirokazu Kameoka, Daichi Kitamura, “Tutorial T-1 Blind audio source
separation on tensor representation,” 2018 IEEE International Conference on Acoustics, Speech and Signal
Processing (ICASSP 2018), April 16th, 2018.
5. Daichi Kitamura, “Blind source separation based on independent low-rank matrix analysis and its
extensions,” Ohio State University, Invited Lecture, December 15th, 2017.
6. Daichi Kitamura, “Dataset: songKitamura,” Dataset for Evaluation of Music Source Separation, October
13th, 2017.
7. Daichi Kitamura, “Acoustic modeling in audio source separation,” The Acoustical Society of Japan, Summer Seminar, Invited Talk, September 11th, 2017.
8. Daichi Kitamura, “Q. Why does a pickup affect on the tone of electric guitars?,” The Journal of the
Acoustical Society of Japan (ASJ), Coffee Break, Q&A Corner, vol. 73, no. 9, September, 2017 (in Japanese).
9. Daichi Kitamura, “Blind source separation based on independent low-rank matrix analysis and its
extension to Student’s t-distribution,” Télécom ParisTech, Invited Lecture, September 4th, 2017.
10. Daichi Kitamura, “Audio source separation based on low-rank structure and statistical independence,”
Nagoya University, Invited Lecture, May 30th, 2017.
11. Daichi Kitamura, “Effective optimization algorithms for blind and supervised music source separation with nonnegative matrix factorization,” SOKENDAI (The Graduate University for Advanced Studies),
Doctoral Dissertation, March, 2017.
12. Daichi Kitamura, “History of independence-based blind source separation and independent low-rankmatrix analysis,” The University of Tokyo, Department of Information Physics and Computing, Invited Talk,
Tokyo, February 27th, 2017.
13. Daichi Kitamura, “Blind source separation based on statistical independence and low-rank matrix decomposition –Independent low-rank matrix analysis–,” University of Tsukuba, Graduate School of Systems
and Information Engineering, Multimedia Laboratory, Invited Talk, Ibaraki, September 26th, 2016.
14. Daichi Kitamura, “Algorithms for independent low-rank matrix analysis,” Supporting document, August, 2016.
15. Daichi Kitamura, “Blind source separation based on independent low-rank matrix analysis,” Speech
PhD Summit 2016, Google inc. London, Invited Poster Presentation, , London, UK, Jun 15th, 2016.

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16. Daichi Kitamura, Nobutaka Ono, “How can we listen only vocal or guitar sound from music? Mechanism in source separation and its capability,” 2016 National Institute of Informatics (NII) Open House,
no. E02, Tokyo, May, 2016.
17. Daichi Kitamura, “History of independent component analysis for sound media signal processing
and its applications,” Hitotsubashi University, Graduate School of International Corporate Strategy, MBA
Program in Financial Strategy, Faculty Seminar, Invited Talk, Tokyo, February 8th, 2016.
18. Daichi Kitamura, “Sound media signal processing for music,” 7th Hokuriku Union Acoustic Seminar,
Beginner’s Meeting, Invited Talk, Kanagawa, December 13th, 2015.
19. Daichi Kitamura, “Generative model in nonnegative matrix factorization and its application to multichannel sound source separation,” Keio University, Science and Technology, Department of Electronics
and Electrical Engineeing, Yukawa Laboratory, Invited Talk, Kanagawa, November 24th, 2015.
20. Daichi Kitamura, Nobutaka Ono, Hiroshi Sawada, Hirokazu Kameoka, Hiroshi Saruwatari, “How can
we listen only vocal or guitar sound from music? Music source separation using nonnegative matrix
factorization,” 2015 National Institute of Informatics (NII) Open House, no. E02, Tokyo, June, 2015.

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