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CharManteau: Character Embedding Models For Portmanteau Creation

2017-07-04EMNLP 2017Code Available0· sign in to hype

Varun Gangal, Harsh Jhamtani, Graham Neubig, Eduard Hovy, Eric Nyberg

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Abstract

Portmanteaus are a word formation phenomenon where two words are combined to form a new word. We propose character-level neural sequence-to-sequence (S2S) methods for the task of portmanteau generation that are end-to-end-trainable, language independent, and do not explicitly use additional phonetic information. We propose a noisy-channel-style model, which allows for the incorporation of unsupervised word lists, improving performance over a standard source-to-target model. This model is made possible by an exhaustive candidate generation strategy specifically enabled by the features of the portmanteau task. Experiments find our approach superior to a state-of-the-art FST-based baseline with respect to ground truth accuracy and human evaluation.

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