Results 51 to 60 of about 24,148,830 (341)

Brains and algorithms partially converge in natural language processing

Communications Biology, 2022
Deep learning algorithms trained to predict masked words from large amount of text have recently been shown to generate activations similar to those of the human brain. However, what drives this similarity remains currently unknown.
Charlotte Caucheteux, J. King
semanticscholar   +1 more source

COVID-Twitter-BERT: A natural language processing model to analyse COVID-19 content on Twitter [PDF]

Frontiers in Artificial Intelligence, 2020
Introduction This study presents COVID-Twitter-BERT (CT-BERT), a transformer-based model that is pre-trained on a large corpus of COVID-19 related Twitter messages. CT-BERT is specifically designed to be used on COVID-19 content, particularly from social
Martin Müller, M. Salathé, P. Kummervold   +2 more
semanticscholar   +1 more source

Stopwords in technical language processing

PLOS ONE, 2021
There are increasing applications of natural language processing techniques for information retrieval, indexing, topic modelling and text classification in engineering contexts. A standard component of such tasks is the removal of stopwords, which are uninformative components of the data. While researchers use readily available stopwords lists that are
Serhad Sarica, Jianxi Luo
openaire   +6 more sources

AllenNLP: A Deep Semantic Natural Language Processing Platform [PDF]

arXiv.org, 2018
Modern natural language processing (NLP) research requires writing code. Ideally this code would provide a precise definition of the approach, easy repeatability of results, and a basis for extending the research.
Matt Gardner, Joel Grus, Mark Neumann, Oyvind Tafjord, Pradeep Dasigi, Nelson F. Liu, Matthew E. Peters, Michael Schmitz, Luke Zettlemoyer   +8 more
semanticscholar   +1 more source

Segment boundary detection directed attention for online end-to-end speech recognition

EURASIP Journal on Audio, Speech, and Music Processing, 2020
Attention-based encoder-decoder models have recently shown competitive performance for automatic speech recognition (ASR) compared to conventional ASR systems.
Junfeng Hou, Wu Guo, Yan Song, Li-Rong Dai   +3 more
doaj   +1 more source

Effective Exploitation of Posterior Information for Attention-Based Speech Recognition

IEEE Access, 2020
End-to-end attention-based modeling is increasingly popular for tackling sequence-to-sequence mapping tasks. Traditional attention mechanisms utilize prior input information to derive attention, which then conditions the output.
Jian Tang, Junfeng Hou, Yan Song, Li-Rong Dai, Ian Mcloughlin   +4 more
doaj   +1 more source

The Genetic-Evolutionary Random Support Vector Machine Cluster Analysis in Autism Spectrum Disorder

IEEE Access, 2019
Previous researches have produced a number of conclusions on the functional magnetic resonance imaging (fMRI) study for autism spectrum disorder (ASD) patients, but there are different opinions about the brain regions of the lesions.
Xia-an Bi, Yingchao Liu, Qi Sun, Xianhao Luo, Haiyan Tan, Jie Chen, Nianyin Zeng   +6 more
doaj   +1 more source

Throughput Optimization for NOMA Cognitive Relay Network with RF Energy Harvesting Based on Improved Bat Algorithm

Mathematics, 2022
Due to the shortcomings of the standard bat algorithm (BA) for multi-parameter optimization, an improved bat algorithm is proposed. The benchmark function test shows that the proposed algorithm has better realization of high-dimensional function ...
Yi Luo, Chenyang Wu, Yi Leng, Nüshan Huang, Lingxi Mao, Junhao Tang   +5 more
doaj   +1 more source

Federated Learning for privacy-Friendly Health Apps: A Case Study on Ovulation Tracking

Journal of Sensor and Actuator Networks
In an era of increasing reliance on digital health solutions, safeguarding user privacy has emerged as a paramount concern. Health applications often need to balance advanced AI functionalities with sufficient privacy measures to ensure user engagement ...
Nikolaos Pavlidis, Andreas Sendros, Theodoros Tsiolakis, Periklis Kostamis, Christos Karasoulas, Eleni Briola, Christos Chrysanthos Nikolaidis, Vasilis Perifanis, George Drosatos, Eleftheria Katsiri, Despoina Elisavet Filippidou, Anastasios Manos, Pavlos S. Efraimidis   +12 more
doaj   +1 more source

Language Invariant Properties in Natural Language Processing

Proceedings of NLP Power! The First Workshop on Efficient Benchmarking in NLP, 2022
Meaning is context-dependent, but many properties of language (should) remain the same even if we transform the context. For example, sentiment, entailment, or speaker properties should be the same in a translation and original of a text. We introduce language invariant properties: i.e., properties that should not change when we transform text, and how
Bianchi, Federico, Nozza, Debora, Hovy, Dirk   +2 more
openaire   +3 more sources