Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Nina Markl"'
Autor:
Claire Cowie, Lauren Hall-Lew, Zuzana Elliott, Anita Klingler, Nina Markl, Stephen Joseph McNulty
Publikováno v:
Frontiers in Artificial Intelligence, Vol 5 (2022)
The COVID-19 pandemic brought about a profound change to the organization of space and time in our daily lives. In this paper we analyze the self-recorded audio/video diaries made by residents of Edinburgh and the Lothian counties during the first na
Externí odkaz:
https://doaj.org/article/e03e1cb15df04297ae51f5100a2afeb9
Autor:
Lauren Hall-Lew, Claire Cowie, Stephen Joseph McNulty, Nina Markl, Shan-Jan Sarah Liu, Catherine Lai, Clare Llewellyn, Beatrice Alex, Nini Fang, Zuzana Elliott, Anita Klingler
Publikováno v:
Journal of Open Humanities Data, Vol 7 (2021)
The ongoing Lothian Diary Project consists of 125+ audio/video recordings collected since May 2020 from residents of Edinburgh and the Lothian counties in Scotland. The diaries comprise self-recorded monologues or semi-structured interviews in which
Externí odkaz:
https://doaj.org/article/b15469b888db48b18dcfe14b47013149
Publikováno v:
New Statesman. 9/15/2017, Vol. 146 Issue 5384, p61-61. 1/2p.
Autor:
Thomas Reitmaier, Electra Wallington, Ondřej Klejch, Nina Markl, Léa-Marie Lam-Yee-Mui, Jennifer Pearson, Matt Jones, Peter Bell, Simon Robinson
Publikováno v:
Reitmaier, T, Wallington, E, Klejch, O, Markl, N, Lam-Yee-Mui, L-M, Pearson, J, Jones, M, Bell, P & Robinson, S 2023, Situating Automatic Speech Recognition Development within Communities of Under-heard Language Speakers . in CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems ., 406, New York, pp. 1-17, ACM CHI 2023 Conference on Human Factors in Computing Systems, Hamburg, Germany, 23/04/23 . https://doi.org/10.1145/3544548.3581385
In this paper we develop approaches to automatic speech recognition (ASR) development that suit the needs and functions of under-heard language speakers. Our novel contribution to HCI is to show how community-engagement can surface key technical and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9a2f0935183291870d77b39f18f5f14
https://doi.org/10.1145/3544548.3581385
https://doi.org/10.1145/3544548.3581385
Autor:
Lauren Hall-Lew, Claire Cowie, Catherine Lai, Nina Markl, Stephen Joseph McNulty, Shan-Jan Sarah Liu, Clare Llewellyn, Beatrice Alex, Zuzana Elliott, Anita Klingler
Publikováno v:
Hall-Lew, L, Cowie, C, Lai, C, Markl, N, McNulty, S, Liu, S-J S, Llewellyn, C, Alex, B, Elliott Slosarova, Z & Klingler, A 2022, ' The Lothian Diary Project : Sociolinguistic methods during the COVID-19 lockdown ', Linguistics Vanguard, vol. 8, no. S3, pp. 321-330 . https://doi.org/10.1515/lingvan-2021-0053
The Lothian Diary Project is an interdisciplinary effort to collect self-recorded audio or video diaries of people’s experiences of COVID-19 in and around Edinburgh, Scotland. In this paper we describe how the project emerged from a desire to suppo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::72a2453b401b26fbf0d3a9bebc07deab
https://doi.org/10.1515/lingvan-2021-0053
https://doi.org/10.1515/lingvan-2021-0053
Autor:
Nina Markl, Mcnulty, Stephen Joseph
Publikováno v:
Nina Markl
Despite the fact that variation is a fundamental characteristic of natural language, automatic speech recognition systems perform systematically worse on non-standardised and marginalised language varieties. In this paper we use the lens of language
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1dce7ea30cec4334762c1ed7aed056ce
Autor:
Nina Markl
Publikováno v:
Markl, N 2022, Language variation and algorithmic bias: understanding algorithmic bias in British English automatic speech recognition . in Proceedings of 2022 5th ACM Conference on Fairness, Accountability, and Transparency (FAccT 2022) . pp. 521-534, 5th Annual ACM Conference on Fairness, Accountability, and Transparency, Seoul, Korea, Democratic People's Republic of, 21/06/22 . https://doi.org/10.1145/3531146.3533117
All language is characterised by variation which language users employ to construct complex social identities and express social meaning. Like other machine learning technologies, speech and language technologies (re)produce structural oppression whe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5585c54ea2a483bbd61dede17ffa6f1c
https://doi.org/10.1145/3531146.3533117
https://doi.org/10.1145/3531146.3533117
Publikováno v:
The Journal of the Acoustical Society of America. 149:A111-A111
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2d5778fd0562d580e2c1cafb51e360c7
https://doi.org/10.1121/10.0004675
https://doi.org/10.1121/10.0004675
Autor:
Nina Markl
Publikováno v:
Nina Markl
Markl, N 2022, Mind the data gap(s): Investigating power in speech and language datasets . in B R Chakravarthi, B Bharathi, J P McCrae, M Zarrouk, K Bali & P Buitelaar (eds), Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion . Dublin, Ireland, pp. 1-12, 2nd Workshop on Language Technology for Equality, Diversity, Inclusion 2022, Dublin, Ireland, 27/05/22 . https://doi.org/10.18653/v1/2022.ltedi-1.1
Markl, N 2022, Mind the data gap(s): Investigating power in speech and language datasets . in B R Chakravarthi, B Bharathi, J P McCrae, M Zarrouk, K Bali & P Buitelaar (eds), Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion . Dublin, Ireland, pp. 1-12, 2nd Workshop on Language Technology for Equality, Diversity, Inclusion 2022, Dublin, Ireland, 27/05/22 . https://doi.org/10.18653/v1/2022.ltedi-1.1
Algorithmic oppression is an urgent and persistent problem in speech and language technologies. Considering power relations embedded in datasets before compiling or using them to train or test speech and language technologies is essential to designin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b3f2c01a8785796677ffe192afebdff8
https://aclanthology.org/2022.ltedi-1.1/
https://aclanthology.org/2022.ltedi-1.1/
Autor:
HALL-LEW, LAUREN, COWIE, CLAIRE, MCNULTY, STEPHEN JOSEPH, MARKL, NINA, LIU, SHAN-JAN SARAH, LAI, CATHERINE, LLEWELLYN, CLARE, ALEX, BEATRICE, FANG, NINI, ELLIOTT, ZUZANA, KLINGLER, ANITA
Publikováno v:
Journal of Open Humanities Data; 2021, Vol. 7 Issue 1, p1-5, 5p