Cross-Lingual Word Embeddings for Turkic Languages
Table 7: Sentiment analysis results on RNN model pre-trained with aligned Uzbek word embeddings. Best results are highlighted in bold. *FastText scores shown in the table are directly taken from the original paper.
['[BOLD] Dataset', '[BOLD] FastText Score*', '[BOLD] Our Score']
The RNN model trained with aligned word embeddings slightly outperforms the same model trained with fastText word embeddings in both the Manual and Translated datasets. This shows that a low-resource language can benefit from the Meemi model when aligned with resource-rich and/or similar languages.