Challenge: a corpus of 16th century letters from and to the Zurich reformer Heinrich Bullinger has been preserved . a recent study investigated code-switching in these 8600 letters .
Approach: They investigate the automatic detection of code-switching in a 16th century letter exchange . they use a popular language identifier to bootstrap a word-based language classifier .
Outcome: The proposed language classifier bootstraps with a popular identifier on a small training corpus of 150 sentences per language.

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Detecting de minimis Code-Switching in Historical German Books (2020.coling-main)

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Challenge: Code-switching has drawn scholarly attention in computational linguistics and natural language processing from many different perspectives.
Approach: They propose to compare informal code-switching to its appearance in more formal registers by annotating and inspecting the German textarchives.
Outcome: The proposed classifiers can help reduce errors when speech recognition is applied to a large corpus with rare embedded languages.
The Decades Progress on Code-Switching Research in NLP: A Systematic Survey on Trends and Challenges (2023.findings-acl)

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Challenge: Code-Switching is a common phenomenon in written text and conversation . it is not so common to observe code-switching in spoken language and not in written language .
Approach: They present a systematic survey on code-switching research in natural language processing to understand the progress of the past decades and conceptualize the challenges and tasks on the topic.
Outcome: The proposed model combines linguistic theories and machine learning techniques to understand the code-switching phenomenon.
Code-Switched Language Identification is Harder Than You Think (2024.eacl-long)

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Challenge: Code switching (CS) is a common phenomenon in written and spoken communication, but is handled poorly by many NLP applications.
Approach: They propose to use CS language identification for corpus building to make it more realistic by scaling it to more languages and considering models with simpler architectures for faster inference.
Outcome: The proposed system is based on a sentence-level multi-label tagging problem and provides recommendations for future work.
The DReaM Corpus: A Multilingual Annotated Corpus of Grammars for the World’s Languages (2020.lrec-1)

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Challenge: Until recently, language descriptions were available in paper form only, with indexes as the only search aid.
Approach: They propose to digitize a multilingual corpus of language descriptions and annotate it with various meta, word, and text attributes to make searching and analysis easier and more useful.
Outcome: The proposed corpus is searchable through a couple of well-established corpus infrastructures.
Automatic Identification of Code-Switching Functions in Speech Transcripts (2023.findings-acl)

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Challenge: Code-switching, or switching between languages, occurs for many reasons and has important linguistic, sociological, and cultural implications.
Approach: They build a system to identify a wide range of functions for which speakers code-switch in everyday speech with an accuracy of 75% . they use a dataset of Hindi-English code-witched data to analyze their results .
Outcome: The proposed system can identify a wide range of functions for which speakers code-switch in everyday speech, with an accuracy of 75% across all functions.
Code-Mixed Probes Show How Pre-Trained Models Generalise on Code-Switched Text (2024.lrec-main)

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Challenge: Code-switching is a prevalent linguistic phenomenon in which multilingual individuals seamlessly alternate between languages.
Approach: They propose to use pre-trained language models to generalise to code-switched text . they use a dataset of well-formed naturalistic code-witched texts and parallel translations into the source languages to examine their results.
Outcome: The proposed model generalises to code-switched text, shedding light on their ability to generalise representations to CS corpora.
Collection and Analysis of Code-switch Egyptian Arabic-English Speech Corpus (L18-1)

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Challenge: despite of the great demand, there is still a huge shortage in available corpora for dialectal languages and code-switched speech.
Approach: They collect conversational Egyptian Arabic spontaneous speech, extract transcriptions and analyze it from a code-switching perspective.
Outcome: The authors collect conversational Egyptian Arabic spontaneous speech, extract transcriptions and analyze speech from the code-switching perspective.
TweetTaglish: A Dataset for Investigating Tagalog-English Code-Switching (2022.lrec-1)

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Challenge: a large dataset is available to study Tagalog-English code-switching in low-resource settings.
Approach: They propose to use a large dataset to investigate Tagalog-English code-switching . they use linguistic data from Tagalogue and Tagalit-English to investigate their results .
Outcome: The proposed dataset achieves a strong performance benchmark for Tagalog-English code-switching.
Cairo Student Code-Switch (CSCS) Corpus: An Annotated Egyptian Arabic-English Corpus (2020.lrec-1)

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Challenge: Code-switching is a phenomenon commonly observed in the Arabicspeaking world . there is still a huge gap in the available resources and NLP applications .
Approach: They propose a corpus of Egyptian- Arabic code-switch speech data that is fully tokenized, lemmatized and annotated for part-of-speech tags.
Outcome: The proposed corpus of Egyptian- Arabic code-switch speech data is fully tokenized, lemmatized and annotated for part-of-speech tags.
Introducing a Parsed Corpus of Historical High German (2024.lrec-main)

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Challenge: outlines the development of the Indiana Parsed Corpus of (Historical) High German . outlines selection of texts, decisions on part-of-speech tags and other labels .
Approach: They propose to build a parsed German corpus that spans Germanic from 1050 to 1950 . they propose to use Penn-style treebanks to capture syntactic relationships between words .
Outcome: The proposed corpus spans Germanic languages from 1050 to 1950 and illustrative annotation issues unique to the language.

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