Papers by Amanuel Mersha

1 papers
Morphology-rich Alphasyllabary Embeddings (2020.lrec-1)

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Challenge: Word embeddings have been successfully trained in many languages, but evaluations in lesser-resourced languages have been cursory and highly variable.
Approach: They propose to build a word embedding model suitable for the Semitic language of Amharic (Ethiopia) it is morphologically rich and written as an alphasyllabary rather than an alphabet .
Outcome: The proposed model performs on word analogy tasks on the Semitic language of Amharic (Ethiopia) it is morphologically rich and written as an alphasyllabary rather than an alphabet .

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