Kazuyoshi Yoshii (Ph.D.)
Title
Team Leader
Members
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Team leaderKazuyoshi Yoshii
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Research scientistAdityaarie Nugraha
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Postdoctoral researcherDiego Dicarlo
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Visiting scientistHidetoshi Shimodaira
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Visiting scientistMakoto Yamada
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Visiting scientistYoshiaki Bando
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Part-time worker IMomose Oyama
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Part-time worker IYihua Zhu
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Part-time worker IYoto Fujita
Introduction
The Sound Scene Understanding team is developing analysis techniques for various kinds of audio signals including speech, music, and environmental sounds. Our approach is to formulate physically- or theoretically-reasonable probabilistic generative models that reflect the characteristics of target signals and solve the inverse problem. We tackle real-world problems by integrating Bayesian learning with deep learning.
Main Research Field
Computer Science
Research Field
Engineering / Mathematics
Research Subjects
Statistical Audio Signal Processing (Source Separation/Localization, Speech Enhancement)
Bayesian Learning (Hierarchical Bayes, Nonparametric Bayes)
Music Information Processing (Source Separation, Automatic Music Transcription)
Bayesian Learning (Hierarchical Bayes, Nonparametric Bayes)
Music Information Processing (Source Separation, Automatic Music Transcription)
Laboratory Website URL
RIKEN Website URL
Introduction Video
Poster(s)
- FY2023 Research Results(PDF 807KB) (Japanese version)
- FY2022 Research Results(PDF 1.16MB)(Japanese version)
- FY2021 Research Results(PDF 1.45MB)(Japanese version)
- FY2019 Research Results (Japanese version)
- FY2018 Research Results (Japanese version)
Related posts
posted on January 27, 2023 10:01Information
posted on July 2, 2021 10:54Seminar
posted on April 16, 2021 11:44Information
