Results 201 to 210 of about 645,699 (249)

Linguistic Markers in At-Risk Mental States Using Natural Language Processing: A Systematic Review. [PDF]

Healthcare (Basel)
Zhang Y, Carrió A, Sevilla-Llewellyn-Jones J, Gutiérrez E, Calvo A, Navarro JB, Barajas A.   +6 more
europepmc   +1 more source

Grammatical error correction for low-resource languages: a review of challenges, strategies, computational and future directions. [PDF]

PeerJ Comput Sci
Marier SM, Chen X, Zhu L, Kong X.
europepmc   +1 more source

Predicting and Synchronising Co-Speech Gestures for Enhancing Human-Robot Interactions Using Deep Learning Models. [PDF]

Biomimetics (Basel)
Fernández-Rodicio E, Dondrup C, Sevilla-Salcedo J, Castro-González Á, Salichs MA.   +4 more
europepmc   +1 more source

Listening for Alzheimer's clues: machine learning analysis of multidomain speech features for cognitive impairment screening. [PDF]

Front Aging Neurosci
Blazquez-Folch J, Calm B, Hinojosa-Calleja A, García-Gutiérrez F, Alegret M, Muñoz N, Cano A, Fernández MV, Miguel A, Solivar A, De Rojas I, Valenzuela-Seba A, García-González P, Puerta R, Olivé C, Capdevila-Bayo M, Muñoz-Morales Á, Bayón-Buján P, Montrreal L, Orellana A, Ortega G, Sanz-Cartagena P, Rosende-Roca M, Cantero-Fortiz Y, Gurruchaga MJ, Tarraga L, Butler C, Montalban X, Boada M, Ruiz A, Marquié M, Valero S.   +31 more
europepmc   +1 more source

Multi-task learning by using contextualized word representations for syntactic parsing of a morphologically rich language. [PDF]

PLoS One
Ehsan T, Butt M, Hussain S, Alhuzali H, Al-Laith A.   +4 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Multilingual POS tagging by a composite deep architecture based on character-level features and on-the-fly enriched Word Embeddings

Knowledge-Based Systems, 2019
Natural Language Processing (NLP) field is taking great advantage from adopting models and methodologies from Artificial Intelligence. In particular, Part-Of-Speech (POS) tagging is a building block for many NLP applications. In this paper, a POS tagging
Fiammetta Marulli, Hamido Fujita, Marco Pota   +2 more
exaly   +2 more sources

PoS Tagging for Classical Chinese Text [PDF]

, 2015
The Chinese language is evolving over the centuries. In order to study the changes of Chinese language using computational methods, segmentation and PoS tagging of Chinese are essential. However, segmentation and PoS tagging methods developed for Modern Standard Chinese do not perform well for Classical Chinese. The cost of segmenting and annotation is
Tin-Shing Chiu, Qin Lu 0001, Jian Xu 0014, Dan Xiong, Fengju Lo   +4 more
openaire   +2 more sources

Part-of-speech (POS) tagging using conditional random field (CRF) model for Khasi corpora

International Journal of Speech Technology, 2021
A K Maji, Partha Pakray, Sunita Warjri   +2 more
exaly   +2 more sources

Improving Data Augmentation for Low-Resource NMT Guided by POS-Tagging and Paraphrase Embedding

ACM Transactions on Asian and Low-Resource Language Information Processing, 2021
Mieradilijiang Maimaiti, Maosong Sun, Huanbo Luan   +2 more
exaly   +2 more sources

Tuning SyntaxNet for POS Tagging Italian Sentences [PDF]

, 2017
SyntaxNet is the NLP framework released by Google in 2016, claimed by its authors as the most accurate dependency parser over across 40 languages beyond English. It relies on a transition-based model implementing POS tagger and dependency parser modules.
Fiammetta Marulli, Marco Pota, Massimo Esposito, Alessandro Maisto, Raffaele Guarasci   +4 more
openaire   +5 more sources