Language Embeddings for Typology and Cross-lingual Transfer Learning

• URL: http://arxiv.org/abs/2106.02082v1
• Date: Thu, 3 Jun 2021 19:00:02 GMT
• Title: Language Embeddings for Typology and Cross-lingual Transfer Learning
• Authors: Dian Yu and Taiqi He and Kenji Sagae
• Abstract summary: We generate dense embeddings for 29 languages using a denoising autoencoder. We evaluate the embeddings using the World Atlas of Language Structures.
• Score: 11.647285195114256
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Cross-lingual language tasks typically require a substantial amount of annotated data or parallel translation data. We explore whether language representations that capture relationships among languages can be learned and subsequently leveraged in cross-lingual tasks without the use of parallel data. We generate dense embeddings for 29 languages using a denoising autoencoder, and evaluate the embeddings using the World Atlas of Language Structures (WALS) and two extrinsic tasks in a zero-shot setting: cross-lingual dependency parsing and cross-lingual natural language inference.

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