# Subtitle Extraction Investigation

## Overview
This script compares different methods and granularity levels for subtitle extraction from video files.

## Installation Requirements

### FFmpeg (Required for Audio Extraction)

**Windows:**
1. Download from: https://ffmpeg.org/download.html
2. Or use winget: `winget install ffmpeg`
3. Or use chocolatey: `choco install ffmpeg`

After installation, restart your terminal and verify:
```powershell
ffmpeg -version
```

## Features

### Granularity Levels
1. **Movie-level**: Entire video summary + full transcript
2. **Second-level**: Time-stamped subtitles by phrase/sentence (MM:SS.mmm)
3. **Word-level**: Individual word timestamps

### Comparison Methods
- **Method A**: Upload video directly to Gemini
- **Method B**: Extract audio with ffmpeg, then upload audio only

## Results Analysis

### Token Usage (from first run - video only):
- **Movie-level**: 15,618 tokens | 32s processing
- **Second-level**: 19,456 tokens | 96s processing
- **Word-level**: 40,279 tokens | 226s processing

### Key Findings:
1. Higher granularity = more tokens + longer processing
2. Word-level is ~2.5x more expensive than movie-level
3. Second-level provides good balance for subtitle generation

## Usage

```bash
# Activate virtual environment
.\venv\Scripts\Activate.ps1

# Run investigation
python backend/investigate_subtitle_extraction.py
```

## Output Files
- `assets/1_processed/subtitle_investigation/*.json` - Individual comparison results
- `complete_comparison.json` - Full comparison data with metadata

## Next Steps
- Install ffmpeg to test Method B (audio extraction)
- Compare audio vs video method performance
- Determine optimal approach for production pipeline