  This paper evaluates morphology-based embeddings for English and Russian
languages. Despite the interest and introduction of several morphology-based
word embedding models in the past and acclaimed performance improvements on
word similarity and language modeling tasks, in our experiments, we did not
observe any stable preference over two of our baseline models - SkipGram and
FastText. The performance exhibited by morphological embeddings is the average
of the two baselines mentioned above.
