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1
Effective healthcare worker-patient communication in Hong Kong accident and emergency departments
In: Hong Kong Journal of Emergency Medicine (HKJEM) (2022)
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2
Structure and Learning (Dagstuhl Seminar 21362)
Dong, Tiansi; Rettinger, Achim; Tang, Jie. - : Dagstuhl Reports. DagRep, Volume 11, Issue 8, 2022
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3
AVQVC: One-shot Voice Conversion by Vector Quantization with applying contrastive learning ...
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4
CREER: A Large-Scale Corpus for Relation Extraction and Entity Recognition ...
Tang, Yu-Siou; Wu, Chung-Hsien. - : arXiv, 2022
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5
Reproducible Subjective Evaluation ...
Morrison, Max; Tang, Brian; Tan, Gefei. - : arXiv, 2022
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6
Compositional Temporal Grounding with Structured Variational Cross-Graph Correspondence Learning ...
Li, Juncheng; Xie, Junlin; Qian, Long. - : arXiv, 2022
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7
Structure and Learning (Dagstuhl Seminar 21362) ...
Dong, Tiansi; Rettinger, Achim; Tang, Jie. - : Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022
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8
Children's acquisition of Mandarin tones in context ...
Tang, Ping. - : Macquarie University, 2022
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9
Children's acquisition of Mandarin tones in context ...
Tang, Ping. - : Macquarie University, 2022
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10
Examining English Ability-Grouping Practices by Aligning CEFR Levels with University-Level General English Courses in Taiwan
In: Sustainability; Volume 14; Issue 8; Pages: 4629 (2022)
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11
A Survey of Automatic Source Code Summarization
In: Symmetry; Volume 14; Issue 3; Pages: 471 (2022)
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12
Improving Recruitment for a Newborn Screening Pilot Study with Adaptations in Response to the COVID-19 Pandemic
In: International Journal of Neonatal Screening; Volume 8; Issue 2; Pages: 23 (2022)
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13
Primary Pupils’ Multimodal Representations in Worksheets—Text Work in Science Education
In: Education Sciences; Volume 12; Issue 3; Pages: 221 (2022)
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14
AWI-CPS analysis and forecast output ...
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15
AWI-CPS analysis and forecast output ...
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16
Disambiguation of morpho-syntactic features of African American English -- the case of habitual be ...
Abstract: Recent research has highlighted that natural language processing (NLP) systems exhibit a bias against African American speakers. The bias errors are often caused by poor representation of linguistic features unique to African American English (AAE), due to the relatively low probability of occurrence of many such features in training data. We present a workflow to overcome such bias in the case of habitual "be". Habitual "be" is isomorphic, and therefore ambiguous, with other forms of "be" found in both AAE and other varieties of English. This creates a clear challenge for bias in NLP technologies. To overcome the scarcity, we employ a combination of rule-based filters and data augmentation that generate a corpus balanced between habitual and non-habitual instances. With this balanced corpus, we train unbiased machine learning classifiers, as demonstrated on a corpus of AAE transcribed texts, achieving .65 F$_1$ score disambiguating habitual "be". ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.2204.12421
https://arxiv.org/abs/2204.12421
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17
Chinese Word Segmentation with Heterogeneous Graph Neural Network ...
Tang, Xuemei; Wang, Jun; Su, Qi. - : arXiv, 2022
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18
Syllabic segmentation of continuous spoken Chinese ...
Tang, Kai Wing.. - : Monash University, 2022
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19
Syllabic segmentation of continuous spoken Chinese ...
Tang, Kai Wing.. - : Monash University, 2022
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20
(18)F-FDG PET/CT and PET/MRI fusion imaging for neuroendocrine carcinoma of the tongue: A case report
In: Radiol Case Rep (2022)
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