Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Eszter Porter"'
Autor:
Simone Graetzer, Michael A. Akeroyd, Jon Barker, Trevor J. Cox, John F. Culling, Graham Naylor, Eszter Porter, Rhoddy Viveros-Muñoz
Publikováno v:
Data in Brief, Vol 41, Iss , Pp 107951- (2022)
This paper presents the Clarity Speech Corpus, a publicly available, forty speaker British English speech dataset. The corpus was created for the purpose of running listening tests to gauge speech intelligibility and quality in the Clarity Project, w
Externí odkaz:
https://doaj.org/article/36bbd811a1fa49d99b3fe8e835f04169
Autor:
Trevor Cox, Michael Akeroyd, Jon Barker, John Culling, Jennifer Firth, Simone Graetzer, Holly Griffiths, Lara Harris, Rhoddy Viveros Munoz, Graham Naylor, Zuzanna Podwinska, Eszter Porter
Publikováno v:
INTER-NOISE and NOISE-CON Congress and Conference Proceedings. 265:4599-4606
Objective speech intelligibility metrics are used to reduce the need for time consuming listening tests. They are used in the design of audio systems; room acoustics and signal processing algorithms. Most published speech intelligibility metrics have
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::308d47b2965124934fe645591da7d81f
https://doi.org/10.3397/in_2022_0662
https://doi.org/10.3397/in_2022_0662
Autor:
Jon Barker, Michael Akeroyd, Trevor J. Cox, John F. Culling, Jennifer Firth, Simone Graetzer, Holly Griffiths, Lara Harris, Graham Naylor, Zuzanna Podwinska, Eszter Porter, Rhoddy Viveros Munoz
Publikováno v:
Interspeech 2022.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d7423426f33af8ec847ac2b729fccb01
https://doi.org/10.21437/interspeech.2022-10821
https://doi.org/10.21437/interspeech.2022-10821
Autor:
Michael A. Akeroyd, Jennifer L. Firth, Graham Naylor, Jon P. Barker, John Culling, Trevor J. Cox, Will Bailey, Simone Graetzer, Rhoddy Viveros Muñoz, Eszter Porter, Holly Griffiths
Publikováno v:
The Journal of the Acoustical Society of America. 153:A48-A48
The clarity enhancement challenges (CECs) seek to facilitate development of novel processing techniques for improving the intelligibility of speech in noise for hearing-aid users through a series of signal-processing challenges. Each challenge provid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cbad5122152d9f181b4f8ca79dde690e
https://doi.org/10.1121/10.0018112
https://doi.org/10.1121/10.0018112
Autor:
Graham Naylor, Eszter Porter, Michael A. Akeroyd, Jon Barker, Trevor J. Cox, John F. Culling, Rhoddy Viveros Muñoz, Simone Graetzer
In recent years, rapid advances in speech technology have been made possible by machine learning challenges such as CHiME, REVERB, Blizzard, and Hurricane. In the Clarity project, the machine learning approach is applied to the problem of hearing aid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a188faa6efeb229a66ccfced647271e8
Autor:
John F. Culling, Michael A. Akeroyd, Jon Barker, Graham Naylor, Trevor J. Cox, Simone Graetzer, Eszter Porter, Rhoddy Viveros Muñoz
Publikováno v:
The Journal of the Acoustical Society of America. 148:2711-2711
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::92525d0b6391702d7854bd264dac3d71
https://doi.org/10.1121/1.5147514
https://doi.org/10.1121/1.5147514