Sentence examples for training sentence from inspiring English sources

Each training sentence is labeled as "1" for a spoken class and "2" for a written class.

For five training sentences, JGMM leads to lower ND values (except for F2M), however, using 10 training sentences, the proposed GB achieves lower or very similar ND values.

The source and target training sentences are assumed to be parallel and phonetically labeled.

Conversion results reported by the authors were obtained using several hundreds of parallel training sentences.

This supports the idea of using a probabilistic model for the errors over training sentences.

Subjects were presented with four training sentences before the test started.

In terms of ND, JGMM leads to lower ND values using 5 training sentences.

This typically results in a highly noisy training set, where many training sentences do not express the intended relation.

In Experiment 1B, the training sentences were no longer grouped into sets of three sentences per creature.

Using 5 training sentences, JGMM leads to the lowest ND values, while En-GB comes in second (except for F2F).

Using 10 training sentences, En-GB leads to the lowest (or very similar to the lowest) ND values.