Abstract:Translanguaging is a new term in bilingual education; it supports a heteroglossic language ideology, which views bilingualism as valuable in its own right. Some translanguaging scholars have questioned the existence of discrete languages, further concluding that multilingualism does not exist. I argue that the political use of language names can and should be distinguished from the social and structural idealizations used to study linguistic diversity, favoring what I call an integrated multilingual model of i… Show more
“…The subject is not easy, however, even for language experts. Many arguments exist about the intricacies of how human brains process language and whether these practices are better described through lenses of code‐switching (MacSwan, ) or translanguaging (Otheguy, García, & Reid, ), among others. While various publications have attempted to outline pedagogical implications of linguistic hybridity, these scholarly arguments raise complex questions that rely on different disciplinary traditions, theoretical models, and ontological framings.…”
“…The subject is not easy, however, even for language experts. Many arguments exist about the intricacies of how human brains process language and whether these practices are better described through lenses of code‐switching (MacSwan, ) or translanguaging (Otheguy, García, & Reid, ), among others. While various publications have attempted to outline pedagogical implications of linguistic hybridity, these scholarly arguments raise complex questions that rely on different disciplinary traditions, theoretical models, and ontological framings.…”
“…Question-question similarity was part of Task 3 on cQA at SemEval-2016/2017(Nakov et al, 2016b, 2017; there was also a similar subtask as part of SemEval-2016 Task 1 on Semantic Textual Similarity (Agirre et al, 2016). Question-question similarity is an important problem with application to question recommendation, question duplicate detection, community question answering, and question answering in general.…”
“…Note that our models are only trained on "pure" English and German utterances; there are no code-switching training examples in the input. Code-switching is a complex linguistic phenomenon and there are different accounts of the socio-linguistic conventions governing its use (Poplack, 2004;Isurin et al, 2009;MacSwan, 2017), as well as of the structural properties of utterances with code-switching (Joshi, 1982). Here we focus on the simple kind of code-switching where a single phrase is produced in a different language than the rest of the utterance.…”
Extending semantic parsing systems to new domains and languages is a highly expensive, time-consuming process, so making effective use of existing resources is critical. In this paper, we describe a transfer learning method using crosslingual word embeddings in a sequence-tosequence model. On the NLmaps corpus, our approach achieves state-of-the-art accuracy of 85.7% for English. Most importantly, we observed a consistent improvement for German compared with several baseline domain adaptation techniques. As a by-product of this approach, our models that are trained on a combination of English and German utterances perform reasonably well on codeswitching utterances which contain a mixture of English and German, even though the training data does not contain any code-switching. As far as we know, this is the first study of code-switching in semantic parsing. We manually constructed the set of code-switching test utterances for the NLmaps corpus and achieve 78.3% accuracy on this dataset.
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