Papers with Arabic-English

3 papers
A Parallel Corpus of Arabic-Japanese News Articles (L18-1)

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Challenge: a large-scale parallel corpora with manually verified subsets of sentences has been used for machine translation between major language pairs.
Approach: They describe the creation process and statistics of the Arabic-Japanese portion of the TUFS Media Corpus . they also report the first results of Arabic-japanese phrase-based machine translation trained on the corpus based on the Arabic corpus.
Outcome: The proposed corpus is a document-level parallel corpus and sentence-level parser corpus . it is the first time that Arabic-Japanese translations have been trained on it .
Improving Language Identification for Code-Switched Speech: The Pivotal Role of Accented English (2026.findings-eacl)

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Challenge: Existing models fail to identify English spoken with the accent of the matrix (dominant) language.
Approach: They propose to fine tune existing LID models with accented English to improve code-switched LID . they use a metric that captures relative ranking of identified languages often overlooked by traditional metrics.
Outcome: The proposed model can be fine tuned with small amounts of accented English without degrading performance on monolingual speech.
Multi-Task Learning for Cross-Lingual Abstractive Summarization (2022.lrec-1)

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Challenge: Existing studies use pseudo cross-lingual abstractive summarization data to train neural encoder-decoders.
Approach: They propose a multi-task learning framework for cross-lingual abstractive summarization that attaches a special token to the beginning of the input sentence to indicate the target task.
Outcome: The proposed model achieves better performance than the model trained with only pseudo cross-lingual abstractive summarization data.

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