Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Thanh Thi Hien Duong"'
Publikováno v:
EAI Endorsed Transactions on Context-aware Systems and Applications, Vol 4, Iss 13, Pp 1-8 (2018)
This paper focuses on solving a challenging speech enhancement problem: improving the desired speech from a single-channel audio signal containing high-level unspecified noise (possibly environmental noise, music, other sounds, etc.). Using source se
Externí odkaz:
https://doaj.org/article/efc2942a74664d8480e1304cc2d9b37f
Publikováno v:
2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC).
Autor:
Phi-Le Nguyen, Quoc Cuong Nguyen, Manh Nguyen Huu, Thanh Thi Hien Duong, Thi-Lan Le, Hai Nghiem Thi
Publikováno v:
MAPR
Real-world video scenes are usually very complicated as they are mixtures of many different audio-visual objects. Humans with normal hearing ability can easily locate, identify and differentiate sound sources which are heard simultaneously. However,
Publikováno v:
EAI Endorsed Transactions on Context-aware Systems and Applications, Vol 4, Iss 13, Pp 1-8 (2018)
This paper focuses on solving a challenging speech enhancement problem: improving the desired speech from a single-channel audio signal containing high-level unspecified noise (possibly environmental noise, music, other sounds, etc.). Using source se
Publikováno v:
IEEE/ACM Transactions on Audio, Speech and Language Processing
IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2019, 27 (1), pp.32-43. ⟨10.1109/TASLP.2018.2869692⟩
IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2019, 27 (1), pp.32-43. ⟨10.1109/TASLP.2018.2869692⟩
International audience; As blind audio source separation has remained very challenging in real-world scenarios, some existing works, including ours, have investigated the use of a weakly-informed approach where generic source spectral models (GSSM) c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70fc37c2309c2b48f5cbe0999da3ed23
https://hal.archives-ouvertes.fr/hal-02045480
https://hal.archives-ouvertes.fr/hal-02045480
Publikováno v:
14th Int. Conf. on Latent Variable Analysis and Signal Separation (LVA ICA)
14th Int. Conf. on Latent Variable Analysis and Signal Separation (LVA ICA), Jul 2018, London, United Kingdom
Latent Variable Analysis and Signal Separation ISBN: 9783319937632
LVA/ICA
14th Int. Conf. on Latent Variable Analysis and Signal Separation (LVA ICA), Jul 2018, London, United Kingdom
Latent Variable Analysis and Signal Separation ISBN: 9783319937632
LVA/ICA
International audience; Nonnegative matrix factorization (NMF) has been well-known as a powerful spectral model for audio signals. Existing work, including ours, has investigated the use of generic source spectral models (GSSM) based on NMF for singl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::679bc8072fe058c43b66016a7cdff47a
https://hal.archives-ouvertes.fr/hal-01740052/file/lvaica_Final.pdf
https://hal.archives-ouvertes.fr/hal-01740052/file/lvaica_Final.pdf
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
APSIPA
We propose novel methods for automatically detecting non-stationary segments using non-negative matrix factorization (NMF) with aiming to effective sound annotation. For acoustic event detection or acoustic scene analysis, preparing a sufficient amou