Translate big blocks of text to get more context
Browse files- translate_transcriptions.py +81 -13
translate_transcriptions.py
CHANGED
@@ -5,6 +5,10 @@ import argparse
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import re
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from tqdm import tqdm
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language_dict = {}
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# Iterate over the LANGUAGE_NAME_TO_CODE dictionary
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for language_name, language_code in LANGUAGE_NAME_TO_CODE.items():
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@@ -19,8 +23,6 @@ for language_name, language_code in LANGUAGE_NAME_TO_CODE.items():
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"translator": language_code
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}
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def translate(transcribed_text, source_languaje, target_languaje, translate_model, translate_tokenizer, device="cpu"):
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# Get source and target languaje codes
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source_languaje_code = language_dict[source_languaje]["translator"]
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@@ -44,26 +46,92 @@ def main(transcription_file, source_languaje, target_languaje, translate_model,
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with open(transcription_file, "r") as f:
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transcription = f.read().splitlines()
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#
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progress_bar = tqdm(total=len(transcription), desc='
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for line in transcription:
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if re.match(r"\d+$", line):
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-
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elif re.match(r"\d\d:\d\d:\d\d,\d+ --> \d\d:\d\d:\d\d,\d+", line):
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-
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elif re.match(r"^$", line):
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-
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else:
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translate_transcription += f"{translated}\n"
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progress_bar.update(1)
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# Save
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output_file = f"{output_folder}/{transcription_file_name}_{target_languaje}.srt"
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with open(output_file, "w") as f:
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f.write(
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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import re
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from tqdm import tqdm
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MAX_LENGTH = 500
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MAGIC_STRING = "[$&]"
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DEBUG = False
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language_dict = {}
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# Iterate over the LANGUAGE_NAME_TO_CODE dictionary
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for language_name, language_code in LANGUAGE_NAME_TO_CODE.items():
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"translator": language_code
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}
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def translate(transcribed_text, source_languaje, target_languaje, translate_model, translate_tokenizer, device="cpu"):
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# Get source and target languaje codes
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source_languaje_code = language_dict[source_languaje]["translator"]
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with open(transcription_file, "r") as f:
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transcription = f.read().splitlines()
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# Concatenate transcriptions
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raw_transcription = ""
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progress_bar = tqdm(total=len(transcription), desc='Concatenate transcriptions progress')
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for line in transcription:
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if re.match(r"\d+$", line):
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pass
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elif re.match(r"\d\d:\d\d:\d\d,\d+ --> \d\d:\d\d:\d\d,\d+", line):
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pass
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elif re.match(r"^$", line):
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pass
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else:
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line = re.sub(r"\[SPEAKER_\d\d\]:", MAGIC_STRING, line)
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raw_transcription += f"{line} "
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progress_bar.update(1)
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progress_bar.close()
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# Save raw transcription
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if DEBUG:
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output_file = f"{output_folder}/{transcription_file_name}_raw.srt"
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with open(output_file, "w") as f:
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f.write(raw_transcription)
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# Split raw transcription
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raw_transcription_list = raw_transcription.split(MAGIC_STRING)
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if raw_transcription_list[0] == "":
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raw_transcription_list = raw_transcription_list[1:]
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# Concatenate transcripts and translate when length is less than MAX_LENGTH
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translated_transcription = ""
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concatenate_transcription = raw_transcription_list[0] + MAGIC_STRING
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progress_bar = tqdm(total=len(raw_transcription_list), desc='Translate transcriptions progress')
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progress_bar.update(1)
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if len(raw_transcription_list) > 1:
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for transcription in raw_transcription_list[1:]:
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if len(concatenate_transcription) + len(transcription) < MAX_LENGTH:
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concatenate_transcription += transcription + MAGIC_STRING
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else:
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translation = translate(concatenate_transcription, source_languaje, target_languaje, translate_model, translate_tokenizer, device)
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translated_transcription += translation
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concatenate_transcription = transcription + MAGIC_STRING
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progress_bar.update(1)
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# Translate last part
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translation = translate(concatenate_transcription, source_languaje, target_languaje, translate_model, translate_tokenizer, device)
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translated_transcription += translation
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else:
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translated_transcription = translate(concatenate_transcription, source_languaje, target_languaje, translate_model, translate_tokenizer, device)
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progress_bar.close()
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# Save translated transcription raw
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if DEBUG:
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output_file = f"{output_folder}/{transcription_file_name}_{target_languaje}_raw.srt"
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with open(output_file, "w") as f:
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f.write(translated_transcription)
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# Read transcription
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with open(transcription_file, "r") as f:
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transcription = f.read().splitlines()
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# Add time stamps
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translated_transcription_time_stamps = ""
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translated_transcription_list = translated_transcription.split(MAGIC_STRING)
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progress_bar = tqdm(total=len(translated_transcription_list), desc='Add time stamps to translated transcriptions progress')
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i = 0
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for line in transcription:
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if re.match(r"\d+$", line):
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translated_transcription_time_stamps += f"{line}\n"
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elif re.match(r"\d\d:\d\d:\d\d,\d+ --> \d\d:\d\d:\d\d,\d+", line):
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translated_transcription_time_stamps += f"{line}\n"
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elif re.match(r"^$", line):
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translated_transcription_time_stamps += f"{line}\n"
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else:
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if (i < len(translated_transcription_list)):
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if translated_transcription_list[i][0] == " ": # Remove space at the beginning
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translated_transcription_list[i] = translated_transcription_list[i][1:]
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speaker = ""
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if re.match(r"\[SPEAKER_\d\d\]:", line):
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speaker = re.match(r"\[SPEAKER_\d\d\]:", line).group(0)
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translated_transcription_time_stamps += f"{speaker} {translated_transcription_list[i]}\n"
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i += 1
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progress_bar.update(1)
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progress_bar.close()
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# Save translated transcription
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output_file = f"{output_folder}/{transcription_file_name}_{target_languaje}.srt"
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with open(output_file, "w") as f:
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f.write(translated_transcription_time_stamps)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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