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2023 EMNLP EMNLP 2023

TongueSwitcher: Fine-Grained Identification of German-English Code-Switching

Abstract

AbstractThis paper contributes to German-English code-switching research. We provide the largest corpus of naturally occurring German-English code-switching, where English is included in German text, and two methods for code-switching identification. The first method is rule-based, using wordlists and morphological processing. We use this method to compile a corpus of 25.6M tweets employing German-English code-switching. In our second method, we continue pretraining of a neural language model on this corpus and classify tokens based on embeddings from this language model. Our systems establish SoTA on our new corpus and an existing German-English code-switching benchmark. In particular, we systematically study code-switching for language-ambiguous words which can only be resolved in context, and morphologically mixed words consisting of both English and German morphemes. We distribute both corpora and systems to the research community.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Deep Learning and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — code-switching identification
🐝 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

Igor Sterner , Simone Teufel

Topics

Artificial Intelligence > Learning Paradigms > Transfer Learning Natural Language Processing > Applications > Text Classification Natural Language Processing > Resources & Methods > Multilingual NLP Machine Learning > Learning Types > Transfer Learning Deep Learning > Models > Large Language Models

Keywords

token classification language model word embedding neural language model morphological processing code-switching identification
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