Papers by Jason Chang

7 papers
TellMeWhy: Learning to Explain Corrective Feedback for Second Language Learners (D19-3)

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Challenge: Write & Improve and Grammarly typically use canned text to explain grammatical errors, but corrective feedback with the most useful explanations may contain collocations, grammar, and contextsensitive examples.
Approach: They propose to analyze sentences with corrections to identify error types and problem words and to extract grammar patterns, collocations and example sentences.
Outcome: The proposed system can be used to customize explanations based on the context of the error.
Cool English: a Grammatical Error Correction System Based on Large Learner Corpora (C18-2)

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Challenge: Existing systems that correct grammatical errors are lacking in second language learning due to limited vocabulary and inadequate command of grammar.
Approach: They propose a grammatical error correction system that provides corrective feedback for essays using a sequence-to-sequence model.
Outcome: The proposed system achieves competitive performance on a number of publicly available testsets.
Generative Dictionary: Improving Language Learner Understanding with Contextual Definitions (2024.emnlp-demo)

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Challenge: GenerativeDictionary generates word sense interpretations based on context . traditional word sense disambiguation methods may not capture the intended word sense .
Approach: They propose a dictionary system that generates word sense interpretations based on context . they transform context sentences to highlight the meaning of target words .
Outcome: The proposed dictionary system is comparable to traditional word sense disambiguation methods.
Learning to Respond to Mixed-code Queries using Bilingual Word Embeddings (N19-4)

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Challenge: Many queries are submitted to search engines on the Web every day to retrieve linguistic information for learning a second language (L2) due to limited L2 vocabulary knowledge, users often submit mix-coded queries without converting them into target language queries.
Approach: They propose a method for learning bilingual word embeddings to support second language learners . mixed-code queries are transformed into target language queries . preliminary evaluation shows method performs reasonablly well .
Outcome: The proposed method performs reasonablly well on a list of common word-translation queries.
Level-Up: Learning to Improve Proficiency Level of Essays (P19-3)

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Challenge: Many essays are submitted to tutoring services by English learners on the Web every day . few systems provide focused suggestions on how to raise the level of proficiency.
Approach: They propose a method for generating suggestions on a sentence for improving proficiency . they propose identifying grammatical elements and ranking related elements to provide suggestions .
Outcome: The proposed method helps english learners improve their writing and reading skills.
Learning to Link Grammar and Encyclopedic Information of Assist ESL Learners (P19-3)

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Challenge: Linggle Booster provides rich lexical information such as collocations and grammar patterns for target words.
Approach: They propose a system that takes an article, identifies target vocabulary, provides lexical information, and generates a quiz on target words.
Outcome: The proposed system has been evaluated on a set of target words and has a good performance.
LanguageNet: Learning to Find Sense Relevant Example Sentences (C18-2)

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Challenge: LanguageNet is a system that can help second language learners to search for different meanings and usages of a word . the polysemy of words, namely words with more than one sense, is one of the major challenges for ESOL learners .
Approach: They propose a system which can help second language learners to search for different meanings of a word.
Outcome: The proposed system can help second language learners to search for different meanings and usages of a word.

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