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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 10 of 10 1 Forensic phonetics and automatic speaker recognition Watt, Dominic; Brown, Georgina. - : Routledge, 2020 BASE Show details 2 General Northern English. Exploring regional variation in the North of England with machine learning Strycharczuk, Patrycja; Lopez-Ibanez, Manu; Brown, Georgina. - 2020 BASE Show details 3 General Northern English. Exploring Regional Variation in the North of England With Machine Learning Strycharczuk, Patrycja; López-Ibáñez, Manuel; Brown, Georgina... In: Front Artif Intell (2020) BASE Show details 4 Investigating the FOOT-STRUT distinction in Northern Englishes using crowdsourced data. Strycharczuk, Patrycja; Brown, Georgina; Leemann, Adrian. - 2019 BASE Show details 5 Investigating the FOOT-STRUT distinction in Northern Englishes using crowdsourced data Brown, Georgina; Strycharczuk, Patjcia; Britain, David... In: Strycharczuk, Patjcia; Brown, Georgina; Leemann, Adrian; Britain, David (2019). Investigating the FOOT-STRUT distinction in Northern Englishes using crowdsourced data. In: 19th International Congress of Phonetic Sciences, Melbourne, Australia, 5 August 2019 - 9 August 2019, 1337-1341. (2019) BASE Show details 6 Segmental Content Effects on Text-dependent Automatic Accent Recognition Brown, Georgina. - : ISCA, 2018 Abstract: This paper investigates the effects of an unknown speech sample’s segmental content (the specific vowels and consonants it contains) on its chances of being successfully classified by an automatic accent recognition system. While there has been some work to investigate this effect in automatic speaker recognition, it has not been explored in relation to automatic accent recognition. This is a task where we would hypothesise that segmental content has a particularly large effect on the likelihood of a successful classification, especially for shorter speech samples. By focussing on one particular text-dependent automatic accent recognition system, the Y-ACCDIST system, we uncover the phonemes that appear to contribute more or less to successful classifications using a corpus of Northern English accents. We also relate these findings to the sociophonetic literature on these specific spoken varieties to attempt to account for the patterns that we see and to consider other factors that might contribute to a sample’s successful classification. URL: https://doi.org/10.21437/Odyssey.2018-2 https://eprints.lancs.ac.uk/id/eprint/124959/1/Odyssey2018GB_revised2.pdf https://eprints.lancs.ac.uk/id/eprint/124959/ BASE Hide details 7 Automatic Sociophonetics:Exploring corpora using a forensic accent recognition system Brown, Georgina; Wormald, Jessica. - 2017 BASE Show details 8 Considering Accent Recognition Technology for Forensic Applications Brown, Georgina. - : University of York, 2017. : Language and Linguistic Science (York), 2017 BASE Show details 9 Automatic recognition of geographically-proximate accents using content-controlled and content-mismatched speech data Brown, Georgina. - : University of Glasgow, 2015 BASE Show details 10 Y-ACCDIST: An Automatic Accent Recognition System for Forensic Applications Brown, Georgina. - : University of York, 2014. : Language and Linguistic Science (York), 2014 BASE Show details

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