Papers with recurrent neural network language model
Identifying and Reducing Gender Bias in Word-Level Language Models (N19-3)
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| Challenge: | Existing discriminatory biases in training data can be amplified by models . text corpora exhibit socially problematic biase . |
| Approach: | They propose a metric to measure gender bias and a regularization loss term to minimize embeddings onto an embeddable subspace that encodes gender. |
| Outcome: | The proposed method reduces gender bias up to an optimal weight assigned to the loss term, and the model becomes unstable as the perplexity increases. |
Personalized Language Model for Query Auto-Completion (P18-2)
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| Challenge: | Query auto-completion (QAC) is a search engine feature that suggests completed queries as the user types . recent work suggests personalization of the recurrent layer to generate personalized completions. |
| Approach: | They propose to use a recurrent neural network language model to generate personalized completions for search engines. |
| Outcome: | The proposed model can generate personalized completions for users not seen during training. |
Recovering Missing Characters in Old Hawaiian Writing (D18-1)
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| Challenge: | Modern Hawaiian orthography includes characters for long vowels and glottal stops . manual transliteration is laborious when performed manually . |
| Approach: | They propose two methods to help transliterate Hawaiian between older and newer texts automatically using finite state transducers and a recurrent neural network language model. |
| Outcome: | The proposed method solves the transliteration problem automatically using finite state transducers and a neural network language model. |