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1
Neural reality of argument structure constructions ...
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2
On the Use of Linguistic Features for the Evaluation of Generative Dialogue Systems ...
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3
TorontoCL at CMCL 2021 Shared Task: RoBERTa with Multi-Stage Fine-Tuning for Eye-Tracking Prediction ...
Li, Bai; Rudzicz, Frank. - : arXiv, 2021
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4
Quantifying the Task-Specific Information in Text-Based Classifications ...
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5
How is BERT surprised? Layerwise detection of linguistic anomalies ...
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6
Semantic coordinates analysis reveals language changes in the AI field ...
Zhu, Zining; Xu, Yang; Rudzicz, Frank. - : arXiv, 2020
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7
Word class flexibility: A deep contextualized approach ...
Li, Bai; Thomas, Guillaume; Xu, Yang. - : arXiv, 2020
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8
To BERT or Not To BERT: Comparing Speech and Language-based Approaches for Alzheimer's Disease Detection ...
Abstract: Research related to automatically detecting Alzheimer's disease (AD) is important, given the high prevalence of AD and the high cost of traditional methods. Since AD significantly affects the content and acoustics of spontaneous speech, natural language processing and machine learning provide promising techniques for reliably detecting AD. We compare and contrast the performance of two such approaches for AD detection on the recent ADReSS challenge dataset: 1) using domain knowledge-based hand-crafted features that capture linguistic and acoustic phenomena, and 2) fine-tuning Bidirectional Encoder Representations from Transformer (BERT)-based sequence classification models. We also compare multiple feature-based regression models for a neuropsychological score task in the challenge. We observe that fine-tuned BERT models, given the relative importance of linguistics in cognitive impairment detection, outperform feature-based approaches on the AD detection task. ... : accepted to INTERSPEECH 2020 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
URL: https://dx.doi.org/10.48550/arxiv.2008.01551
https://arxiv.org/abs/2008.01551
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9
An information theoretic view on selecting linguistic probes ...
Zhu, Zining; Rudzicz, Frank. - : arXiv, 2020
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10
Examining the rhetorical capacities of neural language models ...
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11
Lexical Features Are More Vulnerable, Syntactic Features Have More Predictive Power ...
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12
Representation Learning for Discovering Phonemic Tone Contours ...
Li, Bai; Xie, Jing Yi; Rudzicz, Frank. - : arXiv, 2019
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13
The Effect of Heterogeneous Data for Alzheimer's Disease Detection from Speech ...
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14
Detecting cognitive impairments by agreeing on interpretations of linguistic features ...
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15
Dropout during inference as a model for neurological degeneration in an image captioning network ...
Li, Bai; Zhang, Ran; Rudzicz, Frank. - : arXiv, 2018
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16
Predicting health inspection results from online restaurant reviews ...
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