add separate preprocessing module

nb_samtale.py

@@ -152,7 +152,7 @@ class NBSamtale(datasets.GeneratorBasedBuilder):
             for row in datalines:
                 data = json.loads(row)
                 audio_path = data["file_name"]
-                data["transcription"] = normalize_transcription(data["transcription"], config=self.config.name)
+                data["transcription"] = data[self.config.name]
                 meta[audio_path] = data
 
         id_ = 0
@@ -170,81 +170,3 @@ class NBSamtale(datasets.GeneratorBasedBuilder):
                     id_ += 1
 
 
-### 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 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)
-        t = filter_backslash(t, left=True)
-        t = remove_punctuation(t)
-    # For both, at the end:
-    t = replace_underscore(t)
-    return t

preprocess_transcriptions.py

@@ -0,0 +1,78 @@
+### 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 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)
+        t = filter_backslash(t, left=True)
+        t = remove_punctuation(t)
+    # For both, at the end:
+    t = replace_underscore(t)
+    return t