Results 11 to 20 of about 2,693,181 (220)
Survey Article: Inter-Coder Agreement for Computational Linguistics [PDF]
International Conference on Computational Logic, 2008 This article is a survey of methods for measuring agreement among corpus annotators. It exposes the mathematics and underlying assumptions of agreement coefficients, covering Krippendorff's alpha as well as Scott's pi and Cohen's kappa; discusses the use
Ron Artstein, Massimo Poesio
semanticscholar +3 more sources
Rank diversity of languages: generic behavior in computational linguistics. [PDF]
PLoS One, 2015 Statistical studies of languages have focused on the rank-frequency distribution of words. Instead, we introduce here a measure of how word ranks change in time and call this distribution \emph{rank diversity}.
Cocho G +4 more
europepmc +4 more sources
LFTK: Handcrafted Features in Computational Linguistics [PDF]
Workshop on Innovative Use of NLP for Building Educational Applications, 2023 Past research has identified a rich set of handcrafted linguistic features that can potentially assist various tasks. However, their extensive number makes it difficult to effectively select and utilize existing handcrafted features.
Bruce W. Lee, J. Lee
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The ACL OCL Corpus: advancing Open science in Computational Linguistics [PDF]
Conference on Empirical Methods in Natural Language Processing, 2023 We present ACL OCL, a scholarly corpus derived from the ACL Anthology to assist Open scientific research in the Computational Linguistics domain. Integrating and enhancing the previous versions of the ACL Anthology, the ACL OCL contributes metadata, PDF ...
Shaurya Rohatgi +4 more
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Typos’ Effects on Web-Based Programming Code Output: A Computational Linguistics Study
Theory and Practice in Language Studies, 2022 Computational linguistics is concerned with understanding language from a computational perspective and constructing artifacts that are useful in processing and generating language.
Iksora +4 more
semanticscholar +1 more source
Compositionality in Computational Linguistics
Annual Review of Linguistics, 2022 Neural models greatly outperform grammar-based models across many tasks in modern computational linguistics. This raises the question of whether linguistic principles, such as the Principle of Compositionality, still have value as modeling tools.
L. Donatelli, Alexander Koller
semanticscholar +1 more source
Acoustic compression in Zoom audio does not compromise voice recognition performance
Scientific Reports, 2023 Human voice recognition over telephone channels typically yields lower accuracy when compared to audio recorded in a studio environment with higher quality.
Valeriia Perepelytsia, Volker Dellwo
doaj +1 more source
Schrödinger's tree—On syntax and neural language models
Frontiers in Artificial Intelligence, 2022 In the last half-decade, the field of natural language processing (NLP) has undergone two major transitions: the switch to neural networks as the primary modeling paradigm and the homogenization of the training regime (pre-train, then fine-tune).
Artur Kulmizev +2 more
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Testing the Effectiveness of the Diagnostic Probing Paradigm on Italian Treebanks
Information, 2023 The outstanding performance recently reached by neural language models (NLMs) across many natural language processing (NLP) tasks has steered the debate towards understanding whether NLMs implicitly learn linguistic competence.
Alessio Miaschi +4 more
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The Unstoppable Rise of Computational Linguistics in Deep Learning [PDF]
Annual Meeting of the Association for Computational Linguistics, 2020 In this paper, we trace the history of neural networks applied to natural language understanding tasks, and identify key contributions which the nature of language has made to the development of neural network architectures. We focus on the importance of
J. Henderson
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