Papers with spelling correction models

2 papers
Multi-teacher Distillation for Multilingual Spelling Correction (2023.emnlp-industry)

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Challenge: a multilingual spelling correction model is needed to meet the tight latency requirements of multilingual NLP . a monolingual teacher model is trained for each language/locale, and individual models are distilled into a single student model .
Approach: They propose a multilingual approach to spelling correction using multi-teacher distillation . they train a monolingual teacher model for each language and distill them into a single model .
Outcome: The proposed model can meet the tight latency requirements of deployed services.
Lattice Path Edit Distance: A Romanization-aware Edit Distance for Extracting Misspelling-Correction Pairs from Japanese Search Query Logs (2023.emnlp-industry)

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Challenge: Existing methods to extract misspelling-correction pairs from Japanese query logs are not effective due to the unique input methods.
Approach: They propose a romanization-aware edit distance that utilizes romanization lattices to efficiently consider all possible romanized forms of input strings.
Outcome: Empirical results show lattice path edit distance outperforms standard edit distance in Japanese . latticae path editing distance outpersforms existing methods even with romanization .

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