Sentence examples for trained words from inspiring English sources

At t3, trained words were read faster than untrained words [ t(7) = 4.1, P < 0.005].

A gain of 1 would indicate that the connection strength was equal for trained and untrained words, whereas a gain significantly greater/lower than 1 would indicate stronger/weaker connectivity for trained words relative to untrained words, respectively.

Although we cannot compare the patient and control DCM results directly (because of the difference in stimuli and training), we were able to compare patient (trained words) and control global field power amplitude at each time point using a two-tailed independent samples t-test.

On the other hand, if the two-word lists had a high degree of orthographic overlap, a specific improvement in trained words would be most likely to result from training at the whole-word level.

Post hoc paired t-tests showed that trained words were read significantly faster than untrained words after training at t3 [ t 8) = 4.5, P < 0.005].

The group average reading speed for trained words between t2 and t3 improved by 149 ms, a training effect of 11.5%.

We trained word-based n-gram language models on the 620 million words FidaPLUS corpus of the Slovene language [22], which consists mainly of articles from newspapers and journals.

It's demeaning to do to an intern, or even a specially trained, word-counting horse-prodigy.

A repeated-measures ANOVA on word reading accuracy showed a significant main effect of time [ F 1,8) = 6.9, P < 0.05; average trained word accuracy before training = 91.0%; at t3 = 93.3%], but the critical interaction of time with word list was not significant; both trained and untrained word reading accuracy improved after training.

Compared with word2vec, GloVe requires constructing word word co-occurrence matrix and directly uses it for training word embeddings.

Though word2vec and Glove are different apparently, they essentially use word word co-occurrence to train word embeddings.