Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Eita Nakamura"'
Autor:
Ryota Nakajima, Arata Shirakami, Hayato Tsumura, Kouki Matsuda, Eita Nakamura, Masanori Shimono
Publikováno v:
Communications Biology, Vol 6, Iss 1, Pp 1-14 (2023)
Abstract In the brain, many regions work in a network-like association, yet it is not known how durable these associations are in terms of activity and could survive without structural connections. To assess the association or similarity between brai
Externí odkaz:
https://doaj.org/article/6a4cb90b3ad94aafb90510e63501f030
Publikováno v:
APSIPA Transactions on Signal and Information Processing, Vol 13, Iss 5 (2024)
Externí odkaz:
https://doaj.org/article/aba7196cc38246a6b4aef407d52304d6
Autor:
Rajsuryan Singh, Eita Nakamura
Publikováno v:
Royal Society Open Science, Vol 9, Iss 11 (2022)
We investigate the dynamics of music creation style distributions to understand cultural evolution involving intelligence to create complex artefacts. Previous work suggested that a music creation style can be quantified as statistics describing a ge
Externí odkaz:
https://doaj.org/article/b6c18a53542241ae88a54c5e1b1f1f2a
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1a34691d90a7e325cdb1f07ae912593f
https://doi.org/10.1109/icassp49357.2023.10095462
https://doi.org/10.1109/icassp49357.2023.10095462
Autor:
Ryota Nakajima, Arata Shirakami, Hayato Tsumura, Kouki Matsuda, Eita Nakamura, Masanori Shimono
In the brain, many regions work in a network-like association, yet it is not known how durable these associations are in terms of activity and could survive without structural connections. To assess the association or similarity between brain regions
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::523671777bcd04b0f8ac0ce80636a8a3
https://doi.org/10.1101/2023.03.05.531237
https://doi.org/10.1101/2023.03.05.531237
This paper presents an automatic lyrics transcription (ALT) method for music recordings that leverages the framewise semitone-level sung pitches estimated in a multi-task learning framework. Compared to automatic speech recognition (ASR), ALT is chal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::412e492f8640306b7ff711fd88001ba4
Evolutionary studies have become a dominant thread in the analysis of large audio collections. Such corpora usually consist of musical pieces by various composers or bands and the studies usually focus on identifying general historical trends in harm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64cf2f61deda7efd567b88ac086bc637
Autor:
Eita Nakamura, Kazuyoshi Yoshii
Publikováno v:
Information Sciences. 572:482-500
Most work on musical score models (a.k.a. musical language models) for music transcription has focused on describing the local sequential dependence of notes in musical scores and failed to capture their global repetitive structure, which can be a us
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d73d15899ab0d824bac86693c2dee50
https://doi.org/10.1016/j.ins.2021.04.100
https://doi.org/10.1016/j.ins.2021.04.100
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 28:1644-1655
This article describes a melody harmonization method that generates a sequence of chords (symbols and onset positions) for a given melody (a sequence of musical notes). A typical approach to melody harmonization is to use a hidden Markov model (HMM)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7ef7aba94926566d20a51d6569e2ec1
https://doi.org/10.1109/taslp.2020.2996088
https://doi.org/10.1109/taslp.2020.2996088
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 28:1678-1691
This article describes automatic singing transcription (AST) that estimates a human-readable musical score of a sung melody represented with quantized pitches and durations from a given music audio signal. To achieve the goal, we propose a statistica
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bdab26cf42ab7a2590c229b72453b36c
https://doi.org/10.1109/taslp.2020.2996095
https://doi.org/10.1109/taslp.2020.2996095