Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Publication
Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
Contextual Word Embeddings - Trained On English Wikipedia Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
Contextual Word Embeddings - Trained On English Wikipedia Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
Datasets
This archive contains a collection of computational models called word embeddings. These are vectors that contain numerical representations of words. These have been trained on real language sentences collected from the English Wikipedia. As such, they contain contextual (thematic) knowledge about words (rather than taxonomic).
Taxonomic Word Embeddings - Trained On English Wordnet Random Walk Pseudo-Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
Taxonomic Word Embeddings - Trained On English Wordnet Random Walk Pseudo-Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
Datasets
This archive contains a collection of computational models called word embeddings. These are vectors that contain numerical representations of words. They have been trained on pseudo-sentences generated artificially from a random walk over the English WordNet taxonomy, and thus reflect taxonomic knowledge about words (rather than contextual).
English Wikipedia Corpus Chunks, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
English Wikipedia Corpus Chunks, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher
Datasets
This archive contains a collection of language corpora. These are text files that contain samples of text collected from English Wikipedia.
The Potential Use Of Slow-Down Technology To Improve Pronounciation Of English For International Communication, Bunny Richardson
The Potential Use Of Slow-Down Technology To Improve Pronounciation Of English For International Communication, Bunny Richardson
Doctoral
The focus of this research is on oral communication between L1 (first language) and L2 (second language) English users - to determine whether an algorithm which slows down speech can increase the intelligibility of speech between interlocutors for EIC (English for International Communication). The slow-down facility is a CALL tool which slows down speech without tonal distortion. It allows English language learners more processing time to hear individual phonemes as produced in the stream of connected speech, to help them hear and produce phonemes more accurately and thus more intelligibly. The study involved five tests, all concerned with the intelligibility …
A Generic Framework For Arabic To English Machine Translation Of Simplex Sentences Using The Role And Reference Grammar Linguistic Model, Yasser Salem
Other Resources
No abstract provided.