Papers with target language embedding model

1 papers
Learning and Evaluating Emotion Lexicons for 91 Languages (2020.acl-main)

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Challenge: Emotion lexicons describe the affective meaning of words but are limited in coverage for most languages.
Approach: They propose a method for creating arbitrarily large emotion lexicons for any target language.
Outcome: The proposed method exceeds human reliability for some languages and variables.

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