evo-video-tutorial-indexer

evo-video-tutorial-indexer

A comprehensive skill for extracting chapter indices from tutorial videos using FFmpeg audio extraction, OpenAI Whisper ASR transcription with word-level timestamps, and semantic chapter alignment via fuzzy string matching.

Workflow

1. Extract audio from MP4 using FFmpeg (16kHz mono PCM WAV for optimal Whisper input)
2. Transcribe the audio using OpenAI Whisper with word-level timestamps enabled
3. Analyze transcript words using sliding window fuzzy matching to locate chapter boundaries
4. Align chapter titles to timestamps using multiple matching strategies and keyword heuristics
5. Validate structural requirements (monotonic timestamps, correct count, within duration)
6. Output JSON with video_info and chapters array

Key Alignment Principles

• First chapter always starts at time 0
• Look for explicit verbal cues ("now let's...", "alright first...", "okay so...")
• Chapter timestamp = where speaker FIRST begins sustained discussion of that topic
• Short chapters (Save, Break, Great job!) may be just a few seconds
• Break/Continue pattern: break is a brief interruption, continue resumes same topic
• Timestamps must be strictly monotonically increasing
• All timestamps within [0, duration]
• Word-level timestamps via Whisper's cross-attention DTW provide much better precision than segment-level timestamps

Usage

import sys
sys.path.insert(0, '/app/environment/skills/evo-video-tutorial-indexer/scripts')
from transcribe import extract_audio, transcribe_video
from chapter_detect import detect_chapters, enforce_monotonic
from utils import create_chapter, create_video_index, validate_chapters, write_index

# Step 1: Extract and transcribe
audio_path = extract_audio("/root/tutorial_video.mp4", "/tmp/tutorial_audio.wav")
transcript = transcribe_video(audio_path, model_size="base")

# Step 2: Detect chapters
chapter_titles = ["What we'll do", "How we'll get there", ...]
chapters = detect_chapters(chapter_titles, transcript, duration=1382)

# Step 3: Enforce constraints and validate
chapters = enforce_monotonic(chapters, duration=1382)
errors = validate_chapters(chapters, duration=1382)

# Step 4: Write output
index = create_video_index("In-Depth Floor Plan Tutorial Part 1", 1382, chapters)
write_index(index, '/root/tutorial_index.json')