| Challenge: | Using corpora for second language acquisition has become more and more common . corporata are used to study morpho-syntactic phenomena in English as a foreign language . |
| Approach: | They propose to use a bilingual corpus of French learners of Korean and Korean learners of French to provide a translated and annotated corpus to the scientific community. |
| Outcome: | The proposed corpus can be used for a wide array of purposes in the field of theoretical but also applied linguistics. |
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| Challenge: | Multilingual L2 speech corpora for automatic speech assessment are currently available, but lack comprehensive annotations of L2 from non-native speakers of various languages. |
| Approach: | They propose to use Korean learners’ L2 speech corpus of seven languages to develop automatic speech assessment. |
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Constructing a Dependency Treebank for Second Language Learners of Korean (2024.lrec-main)
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| Challenge: | a manually annotated syntactic treebank is available for second language learners . the dataset includes 7,530 sentences (66,982 words; 129,333 morphemes) |
| Approach: | They propose to manually annotate syntactic treebanks based on Universal Dependencies from Korean written data. |
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A Multilingual Dataset for Evaluating Parallel Sentence Extraction from Comparable Corpora (L18-1)
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| Challenge: | BUCC Shared Task aims to extract parallel sentences from comparable corporad . resulting corpus contains about 3.5 million distinct sentences in english, french, german, Russian, and Chinese . |
| Approach: | They present challenges faced to build a parallel sentences dataset from comparable corporad . they emphasize issues faced to include Chinese as one of the languages . |
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L1-L2 Parallel Treebank of Learner Chinese: Overused and Underused Syntactic Structures (L18-1)
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| Challenge: | Currently, the treebank consists of 600 L2 sentences and 697 L1 sentences. |
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| Outcome: | The proposed treebank consists of 600 L2 sentences and 697 L1 sentences. |
The DReaM Corpus: A Multilingual Annotated Corpus of Grammars for the World’s Languages (2020.lrec-1)
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| Challenge: | Until recently, language descriptions were available in paper form only, with indexes as the only search aid. |
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Augmenting Librispeech with French Translations: A Multimodal Corpus for Direct Speech Translation Evaluation (L18-1)
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| Challenge: | Recent work in spoken language translation (SLT) has attempted to build end-to-end speech-totext translation without using source language transcription during learning or decoding. |
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Korean L2 Vocabulary Prediction: Can a Large Annotated Corpus be Used to Train Better Models for Predicting Unknown Words? (L18-1)
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| Challenge: | a recent study suggests that a classifier trained on unknown words may yield better results for L2 learners. |
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Understanding Cross-Lingual Alignment—A Survey (2024.findings-acl)
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| Challenge: | Cross-lingual alignment is the meaningful similarity of representations across languages in multilingual language models. |
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A Corpus for Multilingual Document Classification in Eight Languages (L18-1)
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| Challenge: | a subset of the Reuters corpus volume 2 is used to evaluate cross-lingual document classification . current best practice is to evaluate document classification on resources in one language and transfer it to another without additional resources. |
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JW300: A Wide-Coverage Parallel Corpus for Low-Resource Languages (P19-1)
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| Challenge: | a shortage of parallel data in low-resource languages creates a bottleneck for cross-lingual transfer . a massive collection of parallel texts for over 300 diverse languages is our main contribution . |
| Approach: | They propose a parallel corpus of over 300 languages with 100 thousand parallel sentences per language pair on average. |
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