NVIDIA
Russian Tagger-based Inverse Text Normalization
Model
NVIDIA
Russian Tagger-based Inverse Text Normalization

Russian single-pass tagger-based model for inverse text normalization based on BERT encoder, trained on 2 mln sentences from Google Text Normalization Dataset, achieves 3.55% WER on Google default test set

  • 1 Version
    1.11.0Selected
    07/21/2022 8:27 PM UTC695.47 MB
    Accuracy
    KeyValue
    DEFAULT TEST (FROM GOOGLE TEXT NORMALIZATION DATASET)3.55% WER, 92.96% SENTENCE ACCURACY
    Model
    KeyValue
    ARCHITECTUREBERT
    INPUTSLIST OF SPOKEN-DOMAIN SENTENCES WITHOUT PUNCTUATION, AS IN ASR OUTPUT
    OUTPUTSLIST OF TAB-SEPARATED TEXT RECORDS, CONSISTING OF 5 COLUMNS, FIRST COLUMN IS THE FINAL WRITTEN-DOMAIN SENTENCE