Sentence examples for selection of training data from inspiring English sources

These ANN models were varied to investigate the influence of variations in the number and the selection of training data.

In this work, emphasis has been focused on intelligent selection of training data, using few training data points and small network.

In this paper, a new approach is proposed based on the selection of training data, where labeled samples highly similar to the target language are put into the training set.

The selection of training data is critical.

In practice, the time- and computation-related constraints were limited to the selection of training data to first 1000 samples.

This could possibly be overcome by the selection of training data targeted towards the domain of older speakers.

To investigate the influence of training data selection and the complementarity of different models, several SEA models were constructed and tested.

However, well-tuned unit selection systems generated with substantially larger amounts of training data compared to SSS systems typically produce more natural speech compared to SSS-based systems.

Moreover, comparing with Random and PPL on each different size of training data, the proposed selections also have lowest perplexity in all cases.

Random Forests is an ensemble of trees created by using bootstrap samples of training data and random feature selection in tree induction [45].

To overcome the scarcity, sparsity, and imbalance of training data, we apply novel feature selection, feature engineering, and feature encoding techniques.