Unsupervised Morphological Expansion of Small Datasets for Improving Word Embeddings
Table 5: Small training samples (Spearman ρ). OOV represents Out of Vocabulary words encountered while testing.
['[BOLD] Language Hindi', '[BOLD] Size 34M', '[BOLD] SG 50.3', '[BOLD] OOV 0', '[BOLD] SG+EXP 56.8', '[BOLD] OOV 0']
The method seems to perform well on small datasets with an increase in accuracy on all datasets across all languages - English, German, French, Spanish, Persian and Hindi. Morphologically richer languages show more increase with respect to others.