Results 61 to 70 of about 182,846 (314)
npj Science of LearningAgeing is associated with elevated pure-tone thresholds, accompanied by increased difficulties in understanding speech-in-noise. While amplification provides important, but insufficient support, auditory-cognitive training (ACT) might propose a solution.
Vanessa Frei, Nathalie Giroud
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Word prediction in computational historical linguistics
Journal of Language Modelling, 2021 In this paper, we investigate how the prediction paradigm from machine learning and Natural Language Processing (NLP) can be put to use in computational historical linguistics. We propose word prediction as an intermediate task, where the forms of unseen
Peter Dekker, Willem Zuidema
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Artificial Intelligence for Bone: Theory, Methods, and Applications
Advanced Intelligent Discovery, EarlyView.Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan +3 more
wiley +1 more source
Scientific ReportsThe multivariate temporal response function (mTRF) is an effective tool for investigating the neural encoding of acoustic and complex linguistic features in natural continuous speech.
Elena Bolt, Nathalie Giroud
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Cognition and Computational Linguistic Creativity
, 2021 Computational creativity is a subfield of artificial intelligence concerned with the development of programs that can produce creative output; in particular, several of these programs deal with linguistic creativity. Many computational creativity systems are modeled after, or inspired by, psychological and cognitive theories of creativity.
Lorenzo Gatti +2 more
openaire +3 more sources
Generating Politically-Relevant Event Data
, 2016 Automatically generated political event data is an important part of the social science data ecosystem. The approaches for generating this data, though, have remained largely the same for two decades.
Beieler, John
core +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
COMPUTATIONAL LINGUISTICS AND ARTIFICIAL INTELLIGENCE [PDF]
Ziglôbitha: Computational linguistics, as an interdisciplinary field combining linguistics and computer science, aims to enable computers to process natural language.
Affas MAAMAR & Hadjer HADJCHERIF
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Linguistic Markers of Influence in Informal Interactions
, 2017 There has been a long standing interest in understanding `Social Influence' both in Social Sciences and in Computational Linguistics. In this paper, we present a novel approach to study and measure interpersonal influence in daily interactions. Motivated
Black, Alan W +5 more
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Large Language Model‐Based Chatbots in Higher Education
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci +4 more
wiley +1 more source