Subword-Level Language Identification for Intra-Word Code-Switching
Table 4: Test set results for entire datasets.
['[EMPTY]', 'DE–TR Seg.', 'DE–TR Tag.', 'DE–TR Char', 'ES–WIX Seg.', 'ES–WIX Tag.', 'ES–WIX Char']
We find the following: (i) For ES–WIX, SegRNN performs slightly better for tagging than the best baseline, both in terms of F1 and character accuracy. For DE–TR, SegRNN and BiLSTM+CRF are the best segmentation models, but the BiLSTM models slightly outperform SegRNN for tagging. (ii) The CRF pipelines perform slightly worse than the best word-level BiLSTM models for both datasets and all evaluations.