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Multi-National Topics Maps for Parliamentary Debate Analysis
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Assessing English language sentences readability using machine learning models
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In: PeerJ Comput Sci (2022)
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Identity-Based Patterns in Deep Convolutional Networks: Generative Adversarial Phonology and Reduplication ...
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G-4 - A pipeline for Hand 2-D Keypoint Localization using Unpaired Image to Image Translation ...
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Rule-based Morphological Inflection Improves Neural Terminology Translation ...
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Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.477/ Abstract: Current approaches to incorporating terminology constraints in machine translation (MT) typically assume that the constraint terms are provided in their correct morphological forms. This limits their application to real-world scenarios where constraint terms are provided as lemmas. In this paper, we introduce a modular framework for incorporating lemma constraints in neural MT (NMT) in which linguistic knowledge and diverse types of NMT models can be flexibly applied. It is based on a novel cross-lingual inflection module that inflects the target lemma constraints based on the source context. We explore linguistically motivated rule-based and data-driven neural-based inflection modules and design English-German health and English-Lithuanian news test suites to evaluate them in domain adaptation and low-resource MT settings. Results show that our rule-based inflection module helps NMT models incorporate lemma constraints more ...
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Keyword:
Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Machine translation; Natural Language Processing
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URL: https://underline.io/lecture/37994-rule-based-morphological-inflection-improves-neural-terminology-translation https://dx.doi.org/10.48448/y0cj-my74
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8 |
Translating Headers of Tabular Data: A Pilot Study of Schema Translation ...
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A Prototype Free/Open-Source Morphological Analyser and Generator for Sakha ...
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Developing Conversational Data and Detection of Conversational Humor in Telugu ...
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Navigating the Kaleidoscope of COVID-19 Misinformation Using Deep Learning ...
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(Mis)alignment Between Stance Expressed in Social Media Data and Public Opinion Surveys ...
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Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach ...
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Rewards with Negative Examples for Reinforced Topic-Focused Abstractive Summarization ...
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Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training ...
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Low-Resource Dialogue Summarization with Domain-Agnostic Multi-Source Pretraining ...
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HittER: Hierarchical Transformers for Knowledge Graph Embeddings ...
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20 |
Ara-Women-Hate: The first Arabic Hate Speech corpus regarding Women ...
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