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.gitattributes

@@ -57,3 +57,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+wavs/*.wav filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1 @@
+.venv/

.python-version

@@ -0,0 +1 @@
+3.11.9

align.py

@@ -0,0 +1,28 @@
+import stable_whisper
+import whisper
+import json
+
+audio_path = "master.mp3"
+transcript_path = "transcript.txt"
+output_path = "aligned_transcription.json"
+
+print("Loading 'medium' model via stable-whisper on GPU...")
+model = stable_whisper.load_model('medium', device='cuda')
+
+print(f"Loading transcript from: {transcript_path}")
+with open(transcript_path, "r", encoding="utf-8") as f:
+    transcript_text = f.read()
+
+
+print(f"Pre-loading audio from: {audio_path}")
+audio_data = whisper.load_audio(audio_path)
+
+print("Aligning audio and text on GPU with stable-whisper...")
+result = model.align(audio_data, transcript_text, language='as')
+
+print(f"Alignment complete. Saving results to {output_path}")
+result_dict = result.to_dict()
+with open(output_path, "w", encoding="utf-8") as f:
+    json.dump(result_dict, f, ensure_ascii=False, indent=2)
+
+print("Process finished. You can download the JSON file from the sidebar.")

master.mp3

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a25b6229ac6901b2859e9a8575cff444bccfe02638a7f77e3b9ce9a57cd2323e
+size 26429231

pyproject.toml

@@ -0,0 +1,12 @@
+[project]
+name = "1hr-demo"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11.9"
+dependencies = [
+    "pydub>=0.25.1",
+    "tts>=0.22.0",
+    "whisper>=1.1.10",
+    "whisper-timestamped>=1.15.9",
+]

segment.py

@@ -0,0 +1,67 @@
+import json
+from pydub import AudioSegment
+import os
+import sys
+
+def segment_audio_from_alignment(audio_path, alignment_path):
+    """
+    Segments a long audio file into chunks based on a word-level
+    timestamped alignment file.
+    """
+    
+    output_dir = "wavs"
+    metadata_path = "metadata.csv"
+    os.makedirs(output_dir, exist_ok=True)
+    
+    print(f"Loading full audio from: {audio_path}")
+    try:
+        full_audio = AudioSegment.from_file(audio_path)
+    except Exception as e:
+        print(f"--- ERROR: Could not load the audio file. ---")
+        print(f"Ensure ffmpeg is correctly installed and the path is correct.")
+        print(f"Details: {e}")
+        sys.exit(1)
+
+    print(f"Loading alignment data from: {alignment_path}")
+    with open(alignment_path, 'r', encoding='utf-8') as f:
+        alignment_data = json.load(f)
+
+    with open(metadata_path, 'w', encoding='utf-8') as metadata_file:
+        print(f"Writing chunks to '{output_dir}' and metadata to '{metadata_path}'...")
+        
+        chunk_counter = 0
+        for segment in alignment_data.get('segments', []):
+            for word_data in segment.get('words', []):
+                start_time = word_data.get('start')
+                end_time = word_data.get('end')
+                text = word_data.get('word', '').strip()
+
+                if start_time is None or end_time is None or not text:
+                    continue
+
+                start_ms = int(start_time * 1000)
+                end_ms = int(end_time * 1000)
+
+                audio_chunk = full_audio[start_ms:end_ms]
+
+                chunk_counter += 1
+                chunk_filename = os.path.join(output_dir, f"chunk_{chunk_counter:05d}.wav")
+
+                audio_chunk.export(chunk_filename, format="wav")
+
+                metadata_file.write(f"{os.path.basename(output_dir)}/{os.path.basename(chunk_filename)}|{text}\n")
+        
+        print(f"Processed {chunk_counter} audio chunks.")
+
+def main():
+    audio_file = "master.mp3"
+    alignment_file = "aligned_transcription.json"
+    
+    if not os.path.exists(audio_file) or not os.path.exists(alignment_file):
+        print("--- ERROR: Make sure 'master.mp3' and 'aligned_transcription.json' are in the project directory. ---")
+        sys.exit(1)
+        
+    segment_audio_from_alignment(audio_file, alignment_file)
+
+if __name__ == "__main__":
+    main()

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