Upload convert_ORTOFON_ORAL13.py

convert_ORTOFON_ORAL13.py

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+# open .data/ORTOFONv1/ortofon_v1_vert.gz
+import gzip
+import os
+import re
+from typing import Dict
+from tqdm import tqdm
+
+FILE_PATH = ".data/ORTOFONv1/ortofon_v1_vert.gz"
+with gzip.open(FILE_PATH, "rt") as f:
+    data = f.read()
+"""
+Problems: 
+- sometimes lines in oral are empty? e.g. 08A009N // REMOVE THESE LINES
+- sometimes lines in ortofon are containing three dots only, such as [mluvčí: Miroslava] ... // REMOVE THESE LINES
+- sometimes lines in ortofon contain @ only, e.g., [mluvčí: Radka] @ // REMOVE THESE LINES
+"""
+
+def process_vert_format_ortofon(vert_content: str) -> Dict[str, str]:
+    # Pattern to match document boundaries and extract metadata
+    doc_pattern = re.compile(r'<doc[^>]*>.*?</doc>', re.DOTALL)
+    metadata_pattern = re.compile(
+        r'<doc id="([^"]*)" year="([^"]*)" month="([^"]*)" location="([^"]*)" situation="([^"]*)" speakers="([^"]*)" genders="([^"]*)" generations="([^"]*)" relationship="([^"]*)"[^>]*>')
+
+    # Pattern to match speaker turns
+    sp_pattern = re.compile(r'<sp[^>]*nickname="([^"]*)"[^>]*>(.*?)</sp>', re.DOTALL)
+
+    # Pattern to match pw tags
+    pw_pattern = re.compile(r'<pw>\n(.*?)</pw>\n', re.DOTALL)
+
+    # Pattern to remove speaker suffix
+    remove_speaker_suffix = re.compile(r'_[0-9]+$')
+
+    # Pattern to remove whitespace before punctuation
+    ws_before_punct = re.compile(r'\s+([.!?])')
+
+    # Find all documents
+    documents = re.findall(doc_pattern, vert_content)
+    processed_documents = {}
+
+    for doc in tqdm(documents):
+        # Extract metadata
+        metadata_match = re.search(metadata_pattern, doc)
+        if metadata_match:
+            doc_id = metadata_match.group(1)
+            location = metadata_match.group(4)
+            situation = metadata_match.group(5)
+            speakers = metadata_match.group(6)
+            genders = metadata_match.group(7)
+            generations = metadata_match.group(8)
+            relationship = metadata_match.group(9)
+            metadata_str = (f"Lokalita: {location}, Situace: {situation}, "
+                            f"Počet mluvčích: {speakers}, Pohlaví: {genders}, "
+                            f"Generace: {generations}, Vztah: {relationship}")
+        else:
+            raise ValueError("Metadata not found in document")
+
+        # Initialize an empty list to hold processed document text
+        processed_document = [metadata_str]
+
+        # Find all speaker turns within the document
+        for sp_match in re.findall(sp_pattern, doc):
+            speaker_id = sp_match[0]
+            # sometimes speaker_id ends with _1, _2, _89, etc. Remove it
+            speaker_id = re.sub(remove_speaker_suffix, '', speaker_id)
+
+            # if speaker is Y, rename him as Jiný zvuk
+            if speaker_id == "Y":
+                speaker_id = "Zvuk"
+
+
+            sp_content = sp_match[1]
+
+            segs = re.findall(pw_pattern, sp_content)
+            if segs == []:
+                segs = [sp_content]
+            # remove tags from each line, and join text
+            tokens = [line.split("\t")[0].strip() for seg in segs for line in seg.split("\n") if line != ""]
+            speaker_text = " ".join(tokens)
+
+            # - sometimes lines in ortofon are containing three dots only, such as [mluvčí: Miroslava] ... // REMOVE THESE LINES
+            if speaker_text.strip() == "...":
+                continue
+            # - sometimes lines in ortofon contain @ only, e.g., [mluvčí: Radka] @ // REMOVE THESE LINES
+            if speaker_text.strip() == "@":
+                continue
+
+            # remove whitespace before ., !, ?
+            speaker_text = re.sub(ws_before_punct, r'\1', speaker_text)
+
+            # Format the speaker turn and add to the processed document list
+            processed_document.append(f"[mluvčí: {speaker_id}] {speaker_text}")
+
+
+        # Join all speaker turns into a single string for the document
+        final_text = '\n'.join(processed_document)
+        processed_documents[doc_id] = final_text
+
+    return processed_documents
+
+
+ortofon_data = process_vert_format_ortofon(data)
+del data
+
+
+FILE_PATH = ".data/ORAL2013/oral2013_vert.gz"
+with gzip.open(FILE_PATH, "rt") as f:
+    data = f.read()
+
+def process_vert_format_oral(vert_content: str) -> Dict[str, str]:
+    # Pattern to match document boundaries and extract metadata
+    doc_pattern = re.compile(r'<doc[^>]*>.*?</doc>', re.DOTALL)
+    metadata_pattern = re.compile(
+        r'<doc id="([^"]*)" temp="([^"]*)" pocet="([^"]*)" vztah="([^"]*)" situace="([^"]*)" promluva="([^"]*)"[^>]*>'
+    )
+    # Pattern to match speaker turns
+    sp_pattern = re.compile(r'<sp[^>]*num="([^"]*)"[^>]*>(.*?)</sp>', re.DOTALL)
+
+    # Pattern to match seg tags
+    seg_pattern = re.compile(r'<seg start="[^"]*" end="[^"]*">(.*?)</seg>\n', re.DOTALL)
+
+    # Pattern to remove whitespace before punctuation
+    ws_before_punct = re.compile(r'\s+([.!?])')
+
+    # Find all documents
+    documents = re.findall(doc_pattern, vert_content)
+    processed_documents = {}
+
+    for doc in tqdm(documents):
+        # Extract metadata
+        metadata_match = re.search(metadata_pattern, doc)
+        if metadata_match:
+            doc_id = metadata_match.group(1)
+            situation = metadata_match.group(5)
+            speakers = metadata_match.group(3)
+            relationship = metadata_match.group(4)
+
+            metadata_str = (f"Situace: {situation}, "
+                            f"Počet mluvčích: {speakers}, "
+                            f"Vztah: {relationship}")
+        else:
+            raise ValueError("Metadata not found in document")
+
+        # Initialize an empty list to hold processed document text
+        processed_document = [metadata_str]
+
+        # Find all speaker turns within the document
+        for sp_match in re.findall(sp_pattern, doc):
+            speaker_id = sp_match[0]
+
+            # if speaker is Y, rename him as Jiný zvuk
+            if speaker_id == "Y":
+                speaker_id = "Zvuk"
+
+            sp_content = sp_match[1]
+            # remove symbols ---, ...:,
+            sp_content = sp_content.replace("---", "")
+            sp_content = sp_content.replace("...:", "")
+            sp_content = sp_content.replace("...", "")
+            sp_content = sp_content.replace("?.", "?")
+
+
+            segs = re.findall(seg_pattern, sp_content)
+            if segs == []:
+                segs = [sp_content]
+            # remove tags from each line, and join text
+            tokens = [line.split("\t")[0].strip() for seg in segs for line in seg.split("\n") if line.strip() != ""]
+            speaker_text = " ".join(tokens)
+
+            # remove whitespace before ., !, ?
+            speaker_text = re.sub(ws_before_punct, r'\1', speaker_text)
+
+            # - sometimes lines in oral are empty? e.g. 08A009N // REMOVE THESE LINES
+            if speaker_text.strip() == "":
+                continue
+
+            # Format the speaker turn and add to the processed document list
+            processed_document.append(f"[mluvčí: {speaker_id}] {speaker_text}")
+
+
+        # Join all speaker turns into a single string for the document
+        final_text = '\n'.join(processed_document)
+        processed_documents[doc_id] = final_text
+
+    return processed_documents
+
+oral_data = process_vert_format_oral(data)
+
+# merge ortofon and oral data
+ortofon_data.update(oral_data)
+
+# save the merged data in jsonlines as {"text": doc, "id": doc_id}
+
+import jsonlines
+FILE_PATH = ".data/hf_dataset/ortofon_oral/test.jsonl"
+
+os.makedirs(os.path.dirname(FILE_PATH), exist_ok=True)
+with jsonlines.open(FILE_PATH, 'w') as writer:
+    for doc_id, doc in ortofon_data.items():
+        writer.write({"text": doc, "id": doc_id})