Evaluation of Morphological Embeddings for English and Russian Languages
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Abstract (arXiv)
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.
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References · 11
- 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
- 2016Enriching Word Vectors with Subword Informationcited by 1,578
- 2014SimLex-999: Evaluating Semantic Models with (Genuine) Similarity Estimationcited by 170
- 2018A Survey of Word Embeddings Evaluation Methodscited by 26
- 2018Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representationscited by 18
- 2016A Joint Model for Word Embedding and Word Morphologycited by 14
- 2014Compositional Morphology for Word Representations and Language Modellingcited by 11
- 2019Morphological Word Embeddingscited by 8
- 2016Morphological Priors for Probabilistic Neural Word Embeddingscited by 6
- 2017The Interplay of Semantics and Morphology in Word Embeddingscited by 6
- 2015Separated by an Un-common Language: Towards Judgment Language Informed Vector Space Modelingcited by 3
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