Spoken dialect identification in Twitter using a multi-filter architecture
Table 3: First filter performance on Leipzig + SwissCrawl corpora
['Language', 'Precision', 'Recall', 'F1-score']
We first evaluate our BERT filter on the test set of the first filter (Leipzig corpora + SwissCrawl). The filter has an F1-score of 99.8% on the GSW test set. However, when this model is applied to Twitter data, we expect a decrease in performance due to having short and also informal messages.