transcribe multilangual inside one file
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@ -108,43 +108,6 @@ def print_speed(current_length):
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print(f" | Speed: {int(trans_speed)} minutes per hour | ", end='', flush=True)
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def write_markdown(file_path, result, postfix=None):
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file_dir = os.path.dirname(file_path)
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txt_folder = os.path.join(file_dir, "Transkription")
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os.makedirs(txt_folder, exist_ok=True)
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base_name = os.path.splitext(os.path.basename(file_path))[0]
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if postfix != None:
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base_name = f"{base_name}_{postfix}"
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output_md = os.path.join(txt_folder, base_name + ".md")
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# Prepare the markdown content.
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folder_name = os.path.basename(file_dir)
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md_lines = [
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f"### {folder_name}",
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f"#### {os.path.basename(file_path)}",
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"---",
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""
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]
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previous_text = ""
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for segment in result["segments"]:
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start = format_timestamp(segment["start"])
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text = segment["text"].strip()
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if previous_text != text: # suppress repeating lines
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md_lines.append(f"`{start}` {text}")
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previous_text = text
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transcript_md = "\n".join(md_lines)
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transcript_md = apply_error_correction(transcript_md)
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transcript_md = remove_lines_with_words(transcript_md)
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with open(output_md, "w", encoding="utf-8") as f:
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f.write(transcript_md)
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print_speed(result["segments"][-1]["end"])
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print(f"... done !")
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def transcribe_file(model, audio_input, language):
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initial_prompt = (
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@ -170,33 +133,85 @@ def detect_language(model, audio):
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print(f"{lang_code}. ", end='', flush=True)
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return lang_code
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def process_file(file_path, model, audio_input):
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"""
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Transcribe the audio file into one markdown file.
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If special case (German sermon in Russian or Russian-marked file), transcribe both in Russian and German into the same file.
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"""
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file_name = os.path.basename(file_path)
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# default values
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postfix = None
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language = detect_language(model, audio_input)
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# Detect spoken language
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detected = detect_language(model, audio_input)
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if language == 'ru' and 'predigt' in file_name.lower() or language == 'de' and 'russisch' in file_name.lower(): # make two files
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# first file
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language="ru"
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postfix = "ru"
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print(f"Transcribing {format_status_path(file_path)} ", end='', flush=True)
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markdown = transcribe_file(model, audio_input, language)
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write_markdown(file_path, markdown, postfix)
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# second file
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language="de"
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postfix = "de"
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elif language == 'en': # songs mostly detect as english
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language="de"
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elif language == 'de' or language == 'ru': # keep as detected
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pass
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else: # not german not english and not russian. --> russina
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language="ru"
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# Determine which languages to transcribe
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if (detected == 'ru' and 'predigt' in file_name.lower()) or \
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(detected == 'de' and 'russisch' in file_name.lower()):
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langs = ['ru', 'de']
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elif detected == 'en': # songs often mis-detected as English
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langs = ['de']
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elif detected in ('de', 'ru'):
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langs = [detected]
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else:
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langs = ['ru']
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# Collect segments for combined result
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combined_segments = []
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for lang in langs:
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print(f"Transcribing {format_status_path(file_path)} as {lang}", end='', flush=True)
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result = transcribe_file(model, audio_input, lang)
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# Insert a synthetic segment for language header
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combined_segments.append({
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'start': 0,
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'text': f"\n## Transcription ({lang.upper()})",
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})
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# Extend with actual segments
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if isinstance(result, dict) and 'segments' in result:
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combined_segments.extend(result['segments'])
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else:
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# If result isn't dict-of-segments, wrap entire text
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text = getattr(result, 'text', None) or (result.get('text') if isinstance(result, dict) else str(result))
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combined_segments.append({'start': 0, 'text': text})
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# Now write out markdown using the combined segments
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file_dir = os.path.dirname(file_path)
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txt_folder = os.path.join(file_dir, "Transkription")
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os.makedirs(txt_folder, exist_ok=True)
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base_name = os.path.splitext(os.path.basename(file_path))[0]
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output_md = os.path.join(txt_folder, base_name + ".md")
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# Build markdown lines
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folder_name = os.path.basename(file_dir)
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md_lines = [
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f"### {folder_name}",
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f"#### {os.path.basename(file_path)}",
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"---",
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""
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]
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previous_text = ""
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for segment in combined_segments:
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start = format_timestamp(segment.get('start', 0))
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text = segment.get('text', '').strip()
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if text and text != previous_text:
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md_lines.append(f"`{start}` {text}")
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previous_text = text
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# Join and post-process
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transcript_md = "\n".join(md_lines)
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transcript_md = apply_error_correction(transcript_md)
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transcript_md = remove_lines_with_words(transcript_md)
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# Write file and report
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with open(output_md, "w", encoding="utf-8") as f:
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f.write(transcript_md)
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if combined_segments:
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end_ts = combined_segments[-1].get('end', combined_segments[-1].get('start', 0))
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print_speed(end_ts)
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print("... done !")
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print(f"Transcribing {format_status_path(file_path)} ", end='', flush=True)
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markdown = transcribe_file(model, audio_input, language)
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write_markdown(file_path, markdown, postfix)
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def process_folder(root_folder):
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"""
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@ -225,10 +240,8 @@ def process_folder(root_folder):
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txt_folder = os.path.join(dirpath, "Transkription")
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base_name = os.path.splitext(os.path.basename(file_path))[0]
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output_md = os.path.join(txt_folder, base_name + ".md")
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output_md_de = os.path.join(txt_folder, base_name + "_de.md")
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output_md_ru = os.path.join(txt_folder, base_name + "_ru.md")
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# skip files with existing md files
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if os.path.exists(output_md) or os.path.exists(output_md_de) or os.path.exists(output_md_ru):
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if os.path.exists(output_md):
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continue
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valid_files.append(file_path)
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