Datasets:
Tasks:
Automatic Speech Recognition
License:
| ### Normalization functions ### | |
| from sprakbanken_normalizer.inverse_text_normalizer import inv_normalize | |
| import re | |
| def filter_backslash(text, left=True): | |
| """Substitute backslash notation with the word to the left or right of it.""" | |
| regx = re.compile(r"\b([\w_-]+)\\([\w_-]+)\b") | |
| if left: | |
| return regx.sub(r"\1", text) | |
| else: | |
| return regx.sub(r"\2", text) | |
| def remove_repeats(text): | |
| """Remove repeated words.""" | |
| return re.sub(r"\b(\w+\s+)(\1){1,10}", "\1", text) | |
| def bracket_metatags(text): | |
| """Enclose unintelligible, foreign, overlapping and unknown words in angle brackets.""" | |
| regx = re.compile(r"%(unint|foreign|unk|overlapping)") | |
| return regx.sub(r"<\1>", text) | |
| def remove_metatags(text): | |
| """Remove metatags for hesitations, laughter, paralinguistic sounds etc.""" | |
| return re.sub(r"%\w+\s", "", text) | |
| def remove_percentage_sign(text): | |
| """Remove percentage sign.""" | |
| return re.sub(r"%", "", text) | |
| def remove_false_starts(text): | |
| """Remove annotations of false starts and interruptions.""" | |
| return re.sub(r"\s\w+£", "", text) | |
| def remove_pound_sign(text): | |
| """Remove pound sign.""" | |
| return re.sub(r"£", "", text) | |
| def replace_underscore(text): | |
| """Replace underscore with a single whitespace.""" | |
| return re.sub(r"_", " ", text) | |
| def remove_punctuation(text): | |
| """Remove punctuation.""" | |
| return re.sub(r"[,\.\!\'-]", "", text) | |
| def normalize_number_words(text): | |
| """Normalize number words to integers.""" | |
| # TODO: convert hyphenated year-words to integers | |
| # TODO: deal with punctuation at the end | |
| inv_norm = inv_normalize(text) | |
| return inv_norm | |
| def normalize_transcription(transcription: str, config="annotations"): | |
| """Normalize transcriptions according to orthographic standards, or verbatim.""" | |
| t = transcription | |
| if config == "annotations": | |
| # Nothing to do, return as is | |
| return t | |
| if config == "orthographic": | |
| t = remove_metatags(t) | |
| t = remove_false_starts(t) | |
| t = re.sub(r"CO-to", "CO2", t) | |
| t = filter_backslash(t, left=False) | |
| t = normalize_number_words(t) | |
| elif config == "verbatim": | |
| t = bracket_metatags(t) | |
| t = remove_percentage_sign(t) | |
| t = remove_pound_sign(t) | |
| t = re.sub(r"C_O-to", "C O to", t) ## NB! "dette C_O-to-pro..." becomes "dette C O topros..." | |
| # TODO: handle hyphens instead of removing them? | |
| t = filter_backslash(t, left=True) | |
| t = remove_punctuation(t) | |
| t = replace_underscore(t) | |
| return t | |