← Back to papers
2021 EACL EACL 2021

Cross-lingual Contextualized Topic Models with Zero-shot Learning

Abstract

AbstractMany data sets (e.g., reviews, forums, news, etc.) exist parallelly in multiple languages. They all cover the same content, but the linguistic differences make it impossible to use traditional, bag-of-word-based topic models. Models have to be either single-language or suffer from a huge, but extremely sparse vocabulary. Both issues can be addressed by transfer learning. In this paper, we introduce a zero-shot cross-lingual topic model. Our model learns topics on one language (here, English), and predicts them for unseen documents in different languages (here, Italian, French, German, and Portuguese). We evaluate the quality of the topic predictions for the same document in different languages. Our results show that the transferred topics are coherent and stable across languages, which suggests exciting future research directions.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — cross-lingual topic model
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Federico Bianchi , Silvia Terragni , Dirk Hovy , Debora Nozza , Elisabetta Fersini

Topics

Artificial Intelligence > Learning Paradigms > Transfer Learning Machine Learning > Core Methods > Clustering Machine Learning > Learning Types > Zero-Shot Learning Natural Language Processing > Resources & Methods > Multilingual NLP Natural Language Processing > Resources & Methods > Transfer Learning Machine Learning > Learning Paradigms > Zero-Shot Learning

Keywords

zero-shot learning transfer learning multilingual nlp topic modeling contextualized embedding multilingual corpus cross-lingual topic model
Download PDF

Related papers

Joint Coreference Resolution and Character Linking for Multiparty Conversation 2021
Progressively Pretrained Dense Corpus Index for Open-Domain Question Answering 2021
Crisscrossed Captions: Extended Intramodal and Intermodal Semantic Similarity Judgments for MS-COCO 2021
Representations for Question Answering from Documents with Tables and Text 2021
Gender and Racial Fairness in Depression Research using Social Media 2021