From Human Judgements to Predictive Models: Unravelling Acceptability in Code-Mixed Sentences

arXiv:2405.05572v1 Announce Type: new
Abstract: Current computational approaches for analysing or generating code-mixed sentences do not explicitly model "naturalness" or "acceptability" of code-mixed sentences, but rely on training corpora to reflect distribution of acceptable code-mixed sentences. Modelling human judgement for the acceptability of code-mixed text can help in distinguishing natural code-mixed text and enable quality-controlled generation of code-mixed text. To this end, we construct Cline - a dataset containing human acceptability judgements for English-Hindi (en-hi) code-mixed text. Cline is the …

abstract arxiv code computational cs.ai cs.cl current distribution human judgement mixed modelling predictive predictive models text training type