The limits of Spanglish?
Linguistic code-switching (C-S) is common in oral bilingual vernacular speech. When used in literature, C-S becomes an artistic choice that can mirror the patterns of bilingual interactions. But it can also potentially exceed them. What are the limits of C-S? We model features of C-S in corpora of contemporary U.S. Spanish-English literary and conversational data to analyze why some critics view the {`}Spanglish{'} texts of Ilan Stavans as deviating from a C-S norm.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
SemEval-2020 Task 9: Overview of Sentiment Analysis of Code-Mixed Tweets
In this paper, we present the results of the SemEval-2020 Task 9 on Sentiment Analysis of Code-Mixed Tweets (SentiMix 2020). We also release and describe our Hinglish (Hindi-English) and Spanglish (Spanish-English) corpo…
Language IdentificationSentenceSentiment AnalysisBAKSA at SemEval-2020 Task 9: Bolstering CNN with Self-Attention for Sentiment Analysis of Code Mixed Text
Sentiment Analysis of code-mixed text has diversified applications in opinion mining ranging from tagging user reviews to identifying social or political sentiments of a sub-population. In this paper, we present an ensem…
General ClassificationOpinion MiningSentiment AnalysisFII-UAIC at SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text Using CNN
The {``}Sentiment Analysis for Code-Mixed Social Media Text{''} task at the SemEval 2020 competition focuses on sentiment analysis in code-mixed social media text , specifically, on the combination of English with Spanis…
Sentiment AnalysisTackling Code-Switched NER: Participation of CMU
Named Entity Recognition plays a major role in several downstream applications in NLP. Though this task has been heavily studied in formal monolingual texts and also noisy texts like Twitter data, it is still an emerging…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)NER+1Improving Bilingual Capabilities of Language Models to Support Diverse Linguistic Practices in Education
Large language models (LLMs) offer promise in generating educational content, providing instructor feedback, and reducing teacher workload on assessments. While prior studies have focused on studying LLM-powered learning…