# Automatic Identification of Motivation for Code-Switching in Speech Transcripts

arXiv: https://arxiv.org/abs/2212.08565 · HTML: https://mlsanity.com/paper/2212.08565/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 47 references that are in the map.
- First posted on arXiv 30 Nov 2022.

## Builds on (most cited first, 18 of 18)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [How multilingual is Multilingual BERT?](https://mlsanity.com/paper/1906.01502/) (2019)
- [Translation Artifacts in Cross-lingual Transfer Learning](https://mlsanity.com/paper/2004.04721/) (2020)
- [CoSDA-ML: Multi-Lingual Code-Switching Data Augmentation for Zero-Shot Cross-Lingual NLP](https://mlsanity.com/paper/2006.06402/) (2020)
- [Are Multilingual Models Effective in Code-Switching?](https://mlsanity.com/paper/2103.13309/) (2021)
- [From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers](https://mlsanity.com/paper/2005.00633/) (2020)
- [Overview for the Second Shared Task on Language Identification in Code-Switched Data](https://mlsanity.com/paper/1909.13016/) (2019)
- [Towards Sub-Word Level Compositions for Sentiment Analysis of Hindi-English Code Mixed Text](https://mlsanity.com/paper/1611.00472/) (2016)
- [A New Dataset for Natural Language Inference from Code-mixed Conversations](https://mlsanity.com/paper/2004.05051/) (2020)
- [Multilingual Code-Switching for Zero-Shot Cross-Lingual Intent Prediction and Slot Filling](https://mlsanity.com/paper/2103.07792/) (2021)
- [Named Entity Recognition on Code-Switched Data: Overview of the CALCS 2018 Shared Task](https://mlsanity.com/paper/1906.04138/) (2019)
- [Can You Traducir This? Machine Translation for Code-Switched Input](https://mlsanity.com/paper/2105.04846/) (2021)
- [From English to Code-Switching: Transfer Learning with Strong Morphological Clues](https://mlsanity.com/paper/1909.05158/) (2019)
- [A Dataset for Building Code-Mixed Goal Oriented Conversation Systems](https://mlsanity.com/paper/1806.05997/) (2018)
- [Code-switching patterns can be an effective route to improve performance of downstream NLP applications: A case study of humour, sarcasm and hate speech detection](https://mlsanity.com/paper/2005.02295/) (2020)
- [SJ_AJ@DravidianLangTech-EACL2021: Task-Adaptive Pre-Training of Multilingual BERT models for Offensive Language Identification](https://mlsanity.com/paper/2102.01051/) (2021)
- [El Volumen Louder Por Favor: Code-switching in Task-oriented Semantic Parsing](https://mlsanity.com/paper/2101.10524/) (2021)

## Built on by (most cited first, 1 of 1)

- [Survey of Cultural Awareness in Language Models: Text and Beyond](https://mlsanity.com/paper/2411.00860/) (2024)

## Abstract (arXiv)

Code-switching, or switching between languages, occurs for many reasons and has important linguistic, sociological, and cultural implications. Multilingual speakers code-switch for a variety of purposes, such as expressing emotions, borrowing terms, making jokes, introducing a new topic, etc. The reason for code-switching may be quite useful for analysis, but is not readily apparent. To remedy this situation, we annotate a new dataset of motivations for code-switching in Spanish-English. We build the first system (to our knowledge) to automatically identify a wide range of motivations that speakers code-switch in everyday speech, achieving an accuracy of 75% across all motivations. Additionally, we show that the system can be adapted to new language pairs, achieving 66% accuracy on a new language pair (Hindi-English), demonstrating the cross-lingual applicability of our annotation scheme