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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 – 16 of 16 1 Identifying preschool measures most predictive of language outcomes at 11 years in the Early Language in Victoria Study ... Gasparini, Loretta. - : Open Science Framework, 2022 BASE Show details 2 A Classification Analysis of the High and Low Levels of Global Competence of Secondary Students: Insights from 25 Countries/Regions Xiaoyue Hu; Jie Hu In: Sustainability ; Volume 13 ; Issue 19 (2021) BASE Show details 3 On the Efficiency of German Growth Forecasts: An Empirical Analysis Using Quantile Random Forests ... Foltas, Alexander; Pierdzioch, Christian. - : Humboldt-Universität zu Berlin, 2020 BASE Show details 4 On the Efficiency of German Growth Forecasts: An Empirical Analysis Using Quantile Random Forests Foltas, Alexander; Pierdzioch, Christian. - : Humboldt-Universität zu Berlin, 2020 BASE Show details 5 Growing Random Forests reveals that exposure and proficiency best account for 2 individual variability in L2 (and L1) brain potentials for syntax and semantics Fromont, Lauren A.; Royle, Phaedra; Steinhauer, Karsten. - : Elsevier, 2020 BASE Show details 6 On the efficiency of German growth forecasts: An empirical analysis using quantile random forests Foltas, Alexander; Pierdzioch, Christian. - : Berlin: Humboldt University Berlin, 2020 BASE Show details 7 Verbing and nouning in French : toward an ecologically valid approach to sentence processing Fromont, Lauren A.. - 2019 BASE Show details 8 Automatic Selection of Parallel Data for Machine Translation Mouratidis, Despoina; Kermanidis, Katia In: IFIP Advances in Information and Communication Technology ; 14th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI) ; https://hal.inria.fr/hal-01821299 ; 14th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), May 2018, Rhodes, Greece. pp.146-156, ⟨10.1007/978-3-319-92016-0_14⟩ (2018) BASE Show details 9 Furosine and HMF determination in prebiotic-supplemented infant formula from Spanish market Sabater, Carlos; Montilla, Antonia; Ovejero, A.. - : Elsevier, 2018 BASE Show details 10 Modelling the interplay of multiple cues in prosodic focus marking Arnhold, Anja; Kyröläinen, Aki-Juhani In: Laboratory Phonology: Journal of the Association for Laboratory Phonology; Vol 8, No 1 (2017); 4 ; 1868-6354 (2017) BASE Show details 11 Predictive modeling of human placement decisions in an English Writing Placement Test Vu, Ngan Hoa In: Graduate Theses and Dissertations (2016) BASE Show details 12 To HAVE and to BE: Function Word Reduction in Child Speech, Child Directed Speech and Inter-adult Speech Barth, Danielle. - : University of Oregon, 2016 BASE Show details 13 Modelling phonetic reduction in a corpus of spoken English using Random Forests and Mixed-Effects Regression Dilts, Philip C. - : University of Alberta. Department of Linguistics., 2013 BASE Show details 14 Modelling phonetic reduction in a corpus of spoken English using Random Forests and Mixed-Effects Regression Dilts, Philip C. - : University of Alberta. Department of Linguistics., 2013 Abstract: Degree: Doctor of Philosophy ; Abstract: In this thesis, phonetic reduction in the Buckeye Corpus (Pitt et al. 2005) of conversational speech is modelled using advanced statistical techniques. Two measures of phonetic reduction are modelled, reduction in the duration of words and deletion of segments from words. Statistical modelling techniques are used to predict how much of each type of reduction is observed in the corpus. Predictor variables are selected from a number of broad classes, including demographic, phonetic, predictability, syntactic, semantic, and pragmatic variables. The broad scope of these variables leads to a generalizable picture of the factors leading to reduction in spontaneous speech. Two modelling techniques with complementary properties are applied to the modelling task: Random Forest (RF) models (Breiman 2001), and Linear Mixed-Effect Regression (LMER) Models. RF models can be used to model complex interactions and highly co-linear predictor variables much more easily than LMER models can. Conversely, LMER models allow each word form and speaker to differ in their response to reduction-predicting variables. LMER models can also easily incorporate predictor variables composed of a large number of unordered categories. Both of these properties of LMER models are effectively impossible to incorporate into current RF models on the scale required for the present study. Results relating to the variables or combinations of variables that correlate with reduction or improve model prediction are described. Possible explanations for the results and implications for the nature of the processes underlying reduction during spontaneous speech are explored. Results relating to the modelling process are also discussed. In particular, random forest modelling indicated that several potential interactions between variables were overlooked in initial LMER modelling. When these interactions were included in a second round of LMER modelling, several were found to improve prediction significantly. The results of the present study may lead to improvements in speech recognition and speech production technologies. The results also suggest that random forests can be used to improve regression models of language data. Keyword: Linguistics; Mixed-Effects Regression; Phonetic Reduction; Phonetics; Random Forests URL: http://hdl.handle.net/10402/era.34065 https://era.library.ualberta.ca/items/ff36bb82-fe70-4a83-b244-96babc2a36bc https://doi.org/10.7939/R3KH0F719 BASE Hide details 15 A random forest system combination approach for error detection in digital dictionaries Rodrigues, Paul; Zajic, David; Doermann, David. - : Association for Computational Linguistics, 2012 BASE Show details 16 A Hybrid approach for biomedical relation extraction using finite state automata and random forest-weighted fusion Liparas, Dimitris; Symeonidis, Spyridon; Vrochidis, Stefanos. - : Springer BASE Show details

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