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Automatic Dialect Density Estimation for African American English ...
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Fairly Accurate: Learning Optimal Accuracy vs. Fairness Tradeoffs for Hate Speech Detection ...
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Mono vs Multilingual BERT: A Case Study in Hindi and Marathi Named Entity Recognition ...
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End-to-end contextual asr based on posterior distribution adaptation for hybrid ctc/attention system ...
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Large-scale Bilingual Language-Image Contrastive Learning ...
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Towards Contextual Spelling Correction for Customization of End-to-end Speech Recognition Systems ...
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Semantic properties of English nominal pluralization: Insights from word embeddings ...
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Informative Causality Extraction from Medical Literature via Dependency-tree based Patterns ...
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NorDiaChange: Diachronic Semantic Change Dataset for Norwegian ...
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Toxicity Detection for Indic Multilingual Social Media Content ...
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Learn from Structural Scope: Improving Aspect-Level Sentiment Analysis with Hybrid Graph Convolutional Networks ...
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Abstract:
Aspect-level sentiment analysis aims to determine the sentiment polarity towards a specific target in a sentence. The main challenge of this task is to effectively model the relation between targets and sentiments so as to filter out noisy opinion words from irrelevant targets. Most recent efforts capture relations through target-sentiment pairs or opinion spans from a word-level or phrase-level perspective. Based on the observation that targets and sentiments essentially establish relations following the grammatical hierarchy of phrase-clause-sentence structure, it is hopeful to exploit comprehensive syntactic information for better guiding the learning process. Therefore, we introduce the concept of Scope, which outlines a structural text region related to a specific target. To jointly learn structural Scope and predict the sentiment polarity, we propose a hybrid graph convolutional network (HGCN) to synthesize information from constituency tree and dependency tree, exploring the potential of linking two ... : 9 pages, 5 figures, 4 tables ...
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Keyword:
Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.2204.12784 https://arxiv.org/abs/2204.12784
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SciNLI: A Corpus for Natural Language Inference on Scientific Text ...
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SHAS: Approaching optimal Segmentation for End-to-End Speech Translation ...
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A New Framework for Fast Automated Phonological Reconstruction Using Trimmed Alignments and Sound Correspondence Patterns ...
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Learning the Ordering of Coordinate Compounds and Elaborate Expressions in Hmong, Lahu, and Chinese ...
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Learning to pronounce as measuring cross-lingual joint orthography-phonology complexity ...
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The Past Mistake is the Future Wisdom: Error-driven Contrastive Probability Optimization for Chinese Spell Checking ...
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