niksss at HinglishEval: Language-agnostic BERT-based Contextual Embeddings with Catboost for Quality Evaluation of the Low-Resource Synthetically Generated Code-Mixed Hinglish Text. (arXiv:2206.08910v1 [cs.CL])

This paper describes the system description for the HinglishEval challenge at
INLG 2022. The goal of this task was to investigate the factors influencing the
quality of the code-mixed text generation system. The task was divided into two
subtasks, quality rating prediction and annotators disagreement prediction of
the synthetic Hinglish dataset. We attempted to solve these tasks using
sentence-level embeddings, which are obtained from mean pooling the
contextualized word embeddings for all input tokens in our text. We
experimented with …

arxiv bert catboost code evaluation generated language mixed quality text