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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 Page: 1 2 3 Hits 1 – 20 of 41 1 Neural reality of argument structure constructions ... Li, Bai; Zhu, Zining; Thomas, Guillaume. - : arXiv, 2022 BASE Show details 2 On the Use of Linguistic Features for the Evaluation of Generative Dialogue Systems ... Berlot-Attwell, Ian; Rudzicz, Frank. - : arXiv, 2021 BASE Show details 3 TorontoCL at CMCL 2021 Shared Task: RoBERTa with Multi-Stage Fine-Tuning for Eye-Tracking Prediction ... Li, Bai; Rudzicz, Frank. - : arXiv, 2021 BASE Show details 4 Quantifying the Task-Specific Information in Text-Based Classifications ... Zhu, Zining; Balagopalan, Aparna; Ghassemi, Marzyeh. - : arXiv, 2021 BASE Show details 5 An {E}valuation of {D}isentangled {R}epresentation {L}earning for {T}exts ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Hirst, Graeme; Rudzicz, Frank. - : Underline Science Inc., 2021 BASE Show details 6 How is BERT surprised? Layerwise detection of linguistic anomalies ... Li, Bai; Zhu, Zining; Thomas, Guillaume. - : arXiv, 2021 BASE Show details 7 Comparing Pre-trained and Feature-Based Models for Prediction of Alzheimer's Disease Based on Speech Balagopalan, Aparna; Eyre, Benjamin; Robin, Jessica... In: Front Aging Neurosci (2021) BASE Show details 8 Identification of primary and collateral tracks in stuttered speech Riad, Rachid; Bachoud-Lévi, Anne-Catherine; Rudzicz, Frank... In: LREC 2020 - 12th Conference on Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-02959454 ; LREC 2020 - 12th Conference on Language Resources and Evaluation, May 2020, Marseille, France (2020) BASE Show details 9 Semantic coordinates analysis reveals language changes in the AI field ... Zhu, Zining; Xu, Yang; Rudzicz, Frank. - : arXiv, 2020 BASE Show details 10 Word class flexibility: A deep contextualized approach ... Li, Bai; Thomas, Guillaume; Xu, Yang. - : arXiv, 2020 BASE Show details 11 To BERT or Not To BERT: Comparing Speech and Language-based Approaches for Alzheimer's Disease Detection ... Balagopalan, Aparna; Eyre, Benjamin; Rudzicz, Frank. - : arXiv, 2020 BASE Show details 12 An information theoretic view on selecting linguistic probes ... Zhu, Zining; Rudzicz, Frank. - : arXiv, 2020 BASE Show details 13 Examining the rhetorical capacities of neural language models ... Zhu, Zining; Pan, Chuer; Abdalla, Mohamed. - : arXiv, 2020 BASE Show details 14 A textual analysis of US corporate social responsibility reports Clarkson, Peter M.; Ponn, Jordan; Richardson, Gordon D.. - : Wiley-Blackwell, 2020 BASE Show details 15 Lexical Features Are More Vulnerable, Syntactic Features Have More Predictive Power ... Novikova, Jekaterina; Balagopalan, Aparna; Shkaruta, Ksenia. - : arXiv, 2019 BASE Show details 16 Representation Learning for Discovering Phonemic Tone Contours ... Li, Bai; Xie, Jing Yi; Rudzicz, Frank. - : arXiv, 2019 BASE Show details 17 Machine learning for MEG during speech tasks Kostas, Demetres; Pang, Elizabeth W.; Rudzicz, Frank. - : Nature Publishing Group UK, 2019 BASE Show details 18 The Effect of Heterogeneous Data for Alzheimer's Disease Detection from Speech ... Balagopalan, Aparna; Novikova, Jekaterina; Rudzicz, Frank; Ghassemi, Marzyeh. - : arXiv, 2018 Abstract: Speech datasets for identifying Alzheimer's disease (AD) are generally restricted to participants performing a single task, e.g. describing an image shown to them. As a result, models trained on linguistic features derived from such datasets may not be generalizable across tasks. Building on prior work demonstrating that same-task data of healthy participants helps improve AD detection on a single-task dataset of pathological speech, we augment an AD-specific dataset consisting of subjects describing a picture with multi-task healthy data. We demonstrate that normative data from multiple speech-based tasks helps improve AD detection by up to 9%. Visualization of decision boundaries reveals that models trained on a combination of structured picture descriptions and unstructured conversational speech have the least out-of-task error and show the most potential to generalize to multiple tasks. We analyze the impact of age of the added samples and if they affect fairness in classification. We also provide ... : Machine Learning for Health (ML4H) Workshop at NeurIPS 2018 arXiv:1811.07216 ... Keyword: Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Machine Learning cs.LG; Machine Learning stat.ML; Sound cs.SD URL: https://dx.doi.org/10.48550/arxiv.1811.12254 https://arxiv.org/abs/1811.12254 BASE Hide details 19 Detecting cognitive impairments by agreeing on interpretations of linguistic features ... Zhu, Zining; Novikova, Jekaterina; Rudzicz, Frank. - : arXiv, 2018 BASE Show details 20 Deconfounding age effects with fair representation learning when assessing dementia ... Zhu, Zining; Novikova, Jekaterina; Rudzicz, Frank. - : arXiv, 2018 BASE Show details Page: 1 2 3

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