Zobrazeno 1 - 10
of 10
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).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2057167a513121762990025be1ae25f
https://doi.org/10.23919/apsipaasc55919.2022.9980162
https://doi.org/10.23919/apsipaasc55919.2022.9980162
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,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a846cb6048f17e6ee430606c4603a59
https://doi.org/10.1109/mapr53640.2021.9585244
https://doi.org/10.1109/mapr53640.2021.9585244
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://explore.openaire.eu/search/publication?articleId=doi_dedup___::e12382ac2e48bea1a9edd14d9a3f230e
http://eudl.eu/doi/10.4108/eai.14-3-2018.154342
http://eudl.eu/doi/10.4108/eai.14-3-2018.154342
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f80ebba71973c9272151e3e5f1b188f0
https://doi.org/10.1109/apsipa.2016.7820760
https://doi.org/10.1109/apsipa.2016.7820760
This book constitutes the refereed proceedings of the First Conference on Intelligence of Things (ICIT 2022), held in Hanoi, Vietnam, in August 2022. A total of 40 full papers in this book have been rigorously peer-reviewed and selected from over 10
This book constitutes the proceedings of the 14th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2018, held in Guildford, UK, in July 2018.The 52 full papers were carefully reviewed and selected from 62 initial s