Machine Learning and Applied Linguistics
This entry introduces the topic of machine learning and provides an overview of its relevance for applied linguistics and language learning. The discussion will focus on giving an introduction to the methods and applications of machine learning in applied linguistics, and will provide references for further study.
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BIG-bench Machine LearningSimilar Papers 제목 키워드 기반
Ethical Questions in NLP Research: The (Mis)-Use of Forensic Linguistics
Ideas from forensic linguistics are now being used frequently in Natural Language Processing (NLP), using machine learning techniques. While the role of forensic linguistics was more benign earlier, it is now being used …
BIG-bench Machine LearningIndonesian Journal of Applied Linguistics: A Bibliometric Portrait of Ten Publication Years
Bibliometric portraits of a single journal appear to be rarely taken in the field of applied linguistics. Viewed from the angles of publication, citation, and indexation, one of the journals worth a bibliometric portrait…
Deep Neural Baselines for Computational Paralinguistics
Detecting sleepiness from spoken language is an ambitious task, which is addressed by the Interspeech 2019 Computational Paralinguistics Challenge (ComParE). We propose an end-to-end deep learning approach to detect and …
Audio ClassificationBIG-bench Machine LearningFeature EngineeringThematic Dispersion in Arabic Applied Linguistics: A Bibliometric Analysis using Brookes' Measure
This study applies Brookes' Measure of Categorical Dispersion (Δ) to analyze the thematic structure of contemporary Arabic Applied Linguistics research. Using a comprehensive, real-world dataset of 1,564 publications fro…
Swiss-AL: A Multilingual Swiss Web Corpus for Applied Linguistics
The Swiss Web Corpus for Applied Linguistics (Swiss-AL) is a multilingual (German, French, Italian) collection of texts from selected web sources. Unlike most other web corpora it is not intended for NLP purposes, but ra…