Papers with BWE

3 papers
Learning Bilingual Sentiment-Specific Word Embeddings without Cross-lingual Supervision (N19-1)

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Challenge: Unsupervised BWE methods are evaluated on word translation or word similarity tasks.
Approach: They propose a method that learns sentiment-specific word representations for two languages in a common space without cross-lingual supervision.
Outcome: The proposed method outperforms previous unsupervised BWE methods and even supervised Bwe methods on three language pairs for cross-lingual sentiment analysis.
Unsupervised Joint Training of Bilingual Word Embeddings (P19-1)

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Challenge: Existing methods for unsupervised bilingual word embeddings are limited by the dissimilarity between the word embedded spaces.
Approach: They propose a method that trains unsupervised bilingual word embeddings jointly on parallel data generated through unsupervised machine translation.
Outcome: The proposed method outperforms unsupervised mapped bilingual word embeddings in cross-lingual NLP tasks.
CIS-BWE: Chaos-Informed Speech Bandwidth Extension (2026.acl-long)

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Challenge: CIS-BWE introduces two chaos-informed discriminators for capturing the deterministic chaos from speech.
Approach: They propose a novel adversarial Bandwidth Extension framework that introduces two chaos-informed discriminators for capturing the deterministic chaos from speech.
Outcome: The proposed framework achieves better performance across nine subjective and objective evaluation metrics with a 40x reduction in discriminator size and overall 0.5x fewer parameters, establishing a new baseline in the BWE task.

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