| import pandas as pd | |
| import os | |
| # --- YOU NEED TO CHANGE THESE TWO LINES --- | |
| # Path to the folder containing your .wav files | |
| audio_folder_path = r'C:/Users/bunny/Downloads/wav' | |
| # Path to your transcript file (metadata.csv) | |
| transcript_file_path = r'C:/Users/bunny/Downloads/metadata.csv' | |
| # --- --- | |
| # 1. Read the transcript file | |
| # It's separated by '|' and has no header, so we name the columns ourselves. | |
| try: | |
| df = pd.read_csv(transcript_file_path, sep='|', header=None, names=['filename', 'transcript']) | |
| except FileNotFoundError: | |
| print(f"Error: The transcript file was not found at '{transcript_file_path}'") | |
| exit() | |
| # 2. Create the full path for each audio file | |
| # os.path.join() correctly combines the folder path and the filename. | |
| df['audio'] = df['filename'].apply(lambda x: os.path.join(audio_folder_path, x)) | |
| # 3. Keep only the columns you want and in the right order | |
| final_df = df[['audio', 'transcript']] | |
| # 4. (Optional) Check which files actually exist and remove rows for missing files | |
| initial_rows = len(final_df) | |
| final_df = final_df[final_df['audio'].apply(os.path.exists)] | |
| removed_rows = initial_rows - len(final_df) | |
| if removed_rows > 0: | |
| print(f"Warning: Removed {removed_rows} rows because the audio file could not be found.") | |
| # 5. Save the final dataset to a new CSV file | |
| output_path = 'final_dataset.csv' | |
| final_df.to_csv(output_path, index=False) | |
| print(f"Successfully created dataset with {len(final_df)} entries.") | |
| print(f"File saved to: {os.path.abspath(output_path)}") | |
| # Display the first 5 rows of your new dataset | |
| print("\n--- Dataset Preview ---") | |
| print(final_df.head()) |