Efficient ASR for Low-Resource Languages: Leveraging Cross-Lingual Unlabeled Data

The article focuses on improving Automatic Speech Recognition (ASR) for languages with limited labeled data. It explores the use of cross-lingual unlabeled data to enhance performance. This is a common and important problem in NLP, and the use of unlabeled data is a key technique for addressing it. The source, ArXiv, suggests this is a research paper.

• •Addresses the challenge of ASR for low-resource languages.
• •Employs cross-lingual unlabeled data to improve performance.
• •Focuses on a key problem in NLP research.