2023 - Research.com Electronics and Electrical Engineering in Japan Leader Award
His scientific interests lie mostly in Blind signal separation, Speech recognition, Independent component analysis, Source separation and Artificial intelligence. His study in Blind signal separation is interdisciplinary in nature, drawing from both Underdetermined system, Algorithm, Frequency domain and Reverberation. His Speech recognition study combines topics in areas such as Smoothing, Transient response and Interference.
His Independent component analysis study integrates concerns from other disciplines, such as Maximum a posteriori estimation and Signal processing. His Source separation research is multidisciplinary, incorporating perspectives in Deconvolution and Time–frequency analysis. The various areas that Shoji Makino examines in his Artificial intelligence study include Estimation theory and Pattern recognition.
The scientist’s investigation covers issues in Speech recognition, Blind signal separation, Artificial intelligence, Acoustics and Independent component analysis. His Speech recognition research incorporates elements of Speech enhancement, Noise, Brain–computer interface and Reverberation. His research in Blind signal separation intersects with topics in Underdetermined system, Source separation, Algorithm, Frequency domain and Signal processing.
Shoji Makino works mostly in the field of Artificial intelligence, limiting it down to topics relating to Pattern recognition and, in certain cases, Cluster analysis and Direction of arrival, as a part of the same area of interest. His studies deal with areas such as Microphone array, Signal, Echo, Microphone and Impulse response as well as Acoustics. Shoji Makino has included themes like Estimation theory and Permutation in his Independent component analysis study.
Shoji Makino mainly investigates Speech recognition, Brain–computer interface, Artificial intelligence, Electroencephalography and Pattern recognition. His research integrates issues of Speech enhancement, Microphone array, Noise reduction and Non-negative matrix factorization in his study of Speech recognition. His work carried out in the field of Microphone array brings together such families of science as Amplitude, Algorithm, Fourier transform and Blind signal separation.
His Artificial intelligence research is multidisciplinary, incorporating elements of Photosensitive epilepsy and Computer vision. Shoji Makino regularly ties together related areas like Source separation in his Pattern recognition studies. The concepts of his Source separation study are interwoven with issues in Independent component analysis, Autoencoder and Spectrogram.
His main research concerns Speech recognition, Brain–computer interface, Electroencephalography, Artificial intelligence and Pattern recognition. Shoji Makino works in the field of Speech recognition, focusing on Speech processing in particular. His Artificial intelligence study frequently links to adjacent areas such as Polynomial.
His Pattern recognition research is multidisciplinary, incorporating perspectives in Artificial neural network, Autoencoder and Source separation. His Microphone array study combines topics in areas such as Acoustics, Speech enhancement, Algorithm and Synchronization. Shoji Makino merges Blind signal separation with Cloud storage in his research.
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A robust and precise method for solving the permutation problem of frequency-domain blind source separation
H. Sawada;R. Mukai;S. Araki;S. Makino.
IEEE Transactions on Speech and Audio Processing (2004)
Jacob Benesty;Shoji Makino;Jingdong Chen.
The fundamental limitation of frequency domain blind source separation for convolutive mixtures of speech
S. Araki;R. Mukai;S. Makino;T. Nishikawa.
IEEE Transactions on Speech and Audio Processing (2003)
Blind speech separation
Shoji Makino;Hiroshi Sawada;Te-Won Lee.
Underdetermined Convolutive Blind Source Separation via Frequency Bin-Wise Clustering and Permutation Alignment
Hiroshi Sawada;Shoko Araki;Shoji Makino.
IEEE Transactions on Audio, Speech, and Language Processing (2011)
Underdetermined blind sparse source separation for arbitrarily arranged multiple sensors
Shoko Araki;Hiroshi Sawada;Ryo Mukai;Shoji Makino.
Signal Processing (2007)
First stereo audio source separation evaluation campaign: data, algorithms and results
Emmanuel Vincent;Hiroshi Sawada;Pau Bofill;Shoji Makino.
international conference on independent component analysis and signal separation (2007)
Polar coordinate based nonlinear function for frequency-domain blind source separation
Hiroshi Sawada;Ryo Mukai;Shoko Araki;Shoji Makino.
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2003)
Exponentially weighted stepsize NLMS adaptive filter based on the statistics of a room impulse response
S. Makino;Y. Kaneda;N. Koizumi.
IEEE Transactions on Speech and Audio Processing (1993)
Common acoustical pole and zero modeling of room transfer functions
Y. Haneda;S. Makino;Y. Kaneda.
IEEE Transactions on Speech and Audio Processing (1994)
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