Music Video

Multi-Camera Music Video Generator

Generate professional AI music videos from a YouTube URL or audio file. The pipeline finds the most powerful moment, cuts it precisely, generates unique cinematic visuals, and adds animated lyrics.

Pipeline Overview

YouTube URL → MP3 → ElevenLabs (word-level timing) → Gemini (listen + build visual plan)
→ Aligned Chorus Cut (20-30s) → 4K Collage → Split 9 Angles → LTX 2.5 Pro Clips → Merge → Remotion Lyrics → Final MP4

Quick Start

Provide: song name + artist (or YouTube URL). Claude runs everything.

Target: 20-30 seconds of the strongest moment (chorus/peak). Default 16:9.

Step 0: Download from YouTube

mkdir -p projects/<slug>/audio
yt-dlp -x --audio-format mp3 --audio-quality 0 \
  -o "projects/<slug>/audio/original.%(ext)s" \
  "ytsearch1:<Artist> <Song> official audio"

Step 1a: Transcribe (Word-Level Timing — GROUND TRUTH)

mkdir -p projects/<slug>/subtitles
cd /Users/aviz/.claude/skills/transcribe/scripts
npx tsx transcribe.ts \
  -i projects/<slug>/audio/original.mp3 \
  -o projects/<slug>/subtitles/words \
  --json

Outputs: subtitles/words (JSON with word timestamps) + subtitles/words.srt

Step 1b: Gemini Audio Analysis (FULL CREATIVE BRIEF)

cd /Users/aviz/ai-music-video-maker/.claude/skills/audio-to-video/scripts
npx ts-node analyze_audio.ts \
  projects/<slug>/audio/original.mp3 \
  30 \
  projects/<slug>/storyboard.md \
  --request "Listen deeply. Find the most powerful, energetic chorus (20-30 seconds). Describe the song's UNIQUE visual identity: color palette, lighting mood, specific aesthetic details. SINGER-FIRST RULE: 60-70% of shots MUST be the singer (ANGLE_2 or ANGLE_8). Only cut to other instruments/crowd during clear instrumental breaks with no vocals. For ALL singer shots, the prompt MUST include 'mouth open singing, lip sync, close-up face' so LTX 2.5 generates synchronized mouth movement. For each shot: write a vivid cinematic PROMPT. Pattern: singer (4s) → brief cutaway (2s) → singer (4s) → brief cutaway (2s). NEVER generic — be hyper-specific to THIS song's vibe."

Gemini's job: Listen to the music, understand the song's unique identity, build shot-specific prompts that bring THAT song to life. It outputs a storyboard with timing + custom prompts per shot.

Step 1c: Align Timing (ElevenLabs → Ground Truth)

Gemini gives approximate timing. Refine using word-level JSON:

python3 << 'EOF'
import json
with open('projects/<slug>/subtitles/words', 'r') as f:
    data = json.load(f)

# Explore structure first
print("Keys:", list(data.keys()))

# Find words near Gemini's suggested chorus start
target = <GEMINI_START_SECONDS>
words = data.get('words', data.get('alignment', {}).get('words', []))
for w in words:
    t = w.get('start', w.get('startTime', 0))
    if abs(t - target) < 8:
        print(f"{t:.3f}s  {w.get('word','')}")
EOF

Use the exact word timestamp as the real cut point.

Step 2: Create Audio Chunks

Split the chorus into clips of 3-5 seconds each (LTX 2.5 Pro limit: max 10s per clip):

mkdir -p projects/<slug>/audio/chunks
# For a 25-second chorus starting at 42.3s, create 6 chunks of ~4s:
ffmpeg -i projects/<slug>/audio/original.mp3 -ss 42.300 -t 4.0 -y projects/<slug>/audio/chunks/chunk_01.mp3
ffmpeg -i projects/<slug>/audio/original.mp3 -ss 46.300 -t 4.0 -y projects/<slug>/audio/chunks/chunk_02.mp3
# etc.

Step 3: Generate 4K Collage

Gemini builds this prompt based on the song. Include the Gemini-generated visual identity in the prompt.

mkdir -p projects/<slug>/images/angles
cd /Users/aviz/.claude/skills/image-generation/scripts
npx ts-node generate_poster.ts \
  -d projects/<slug>/images/collage.jpg \
  -a 16:9 -q 2K \
  "<GEMINI_GENERATED_COLLAGE_PROMPT>"

Collage prompt MUST include:

• Artist's specific look (hair, outfit, stage presence)
• Song's unique color palette
• Specific lighting design (not generic "concert lights")
• 9 distinct action frames — each mid-motion, NO static poses
• "SEAMLESS ZERO borders between frames"
• Varied subjects: singer, guitarist, drummer, bassist, crowd, silhouette, wide, low-angle, behind-band

Step 4: Split Collage → 9 Angles

bash /Users/aviz/ai-music-video-maker/.claude/skills/music-video/scripts/split_collage.sh \
  projects/<slug>/images/collage.jpg \
  projects/<slug>/images/angles/

Creates angle_1.jpg through angle_9.jpg

Step 5: Generate Video Clips (LTX 2.5 Pro)

mkdir -p projects/<slug>/videos/clips
cd /Users/aviz/ai-music-video-maker/.claude/skills/audio-to-video/scripts

npx ts-node generate.ts \
  --audio projects/<slug>/audio/chunks/chunk_01.mp3 \
  --image projects/<slug>/images/angles/angle_2.jpg \
  -d projects/<slug>/videos/clips/shot_01.mp4 \
  "<GEMINI_GENERATED_SHOT_PROMPT_FOR_CHUNK_01>"

Rules:

• SINGER-FIRST: 60-70% of shots must be singer (ANGLE_2 or ANGLE_8) — when vocals are heard, always use singer angle
• Only cut away to instruments/crowd during clear instrumental breaks (no vocals)
• NEVER repeat same angle in consecutive shots
• Each prompt must describe: subject action + camera movement + lighting event + emotion
• Singer shot prompts MUST include: "mouth open singing, lip sync, close-up face" — this drives LTX audio sync
• Non-singer shots are brief (2-3s) transitions between singer shots, not main content
• Pattern: singer (4s) → wide/instrument (2s) → singer (4s) → crowd (2s) → singer (4s)

Step 6: Merge with Continuous Audio

# Concat list — use original clips/ (fps handled by Remotion at Step 7)
ls projects/<slug>/videos/clips/shot_*.mp4 | sort | \
  awk '{print "file \047"$0"\047"}' > /tmp/concat_<slug>.txt

# Join videos (no audio)
ffmpeg -f concat -safe 0 -i /tmp/concat_<slug>.txt -an -c:v copy \
  projects/<slug>/videos/video_only.mp4

# Extract original continuous audio for the segment
CHORUS_START=<aligned_start>
TOTAL_DUR=$(ffprobe -v error -show_entries format=duration -of csv=p=0 \
  projects/<slug>/videos/video_only.mp4)
ffmpeg -i projects/<slug>/audio/original.mp3 \
  -ss $CHORUS_START -t $TOTAL_DUR \
  -y projects/<slug>/audio/chorus_audio.mp3

# Mux + fade out
FADE_START=$(echo "$TOTAL_DUR - 2" | bc)
ffmpeg -i projects/<slug>/videos/video_only.mp4 \
  -i projects/<slug>/audio/chorus_audio.mp3 \
  -vf "fade=t=out:st=${FADE_START}:d=2" \
  -af "afade=t=out:st=${FADE_START}:d=2" \
  -c:v libx264 -c:a aac -shortest \
  projects/<slug>/videos/merged.mp4

# CRITICAL for Remotion: re-encode with all keyframes (g=1) for frame-accurate seeking
# Without this, Remotion will produce choppy output
ffmpeg -i projects/<slug>/videos/merged.mp4 \
  -c:v libx264 -g 1 -keyint_min 1 -sc_threshold 0 \
  -c:a copy \
  -y projects/<slug>/videos/merged_remotion.mp4

Step 7: Remotion Lyrics Overlay (MANDATORY)

Setup

REMOTION=/Users/aviz/remotion-assistant
SLUG=<slug>

# Copy assets — use merged_remotion.mp4 (all-keyframe version for Remotion seeking)
cp projects/$SLUG/videos/merged_remotion.mp4 $REMOTION/public/videos/${SLUG}.mp4
cp projects/$SLUG/subtitles/words $REMOTION/public/lyrics/${SLUG}.json

Choose style based on song genre:

Create composition

// $REMOTION/src/compositions/Temp_<Slug>.tsx
import { LyricsOverlay, parseElevenLabsTranscript } from './LyricsOverlay';
import { shiftLyricsTiming } from '../utils/lyricsParser';
import { staticFile } from 'remotion';

const transcript = require('../../public/lyrics/<slug>.json');

const CHORUS_START = <CHORUS_START_SECONDS>;

export const Temp_<Slug>: React.FC = () => {
  // CRITICAL: filter to only words at/after chorus start BEFORE parsing
  // Without this, pre-chorus words get clamped to t=0 and all appear at frame 0
  const filteredTranscript = {
    ...transcript,
    words: (transcript.words || []).filter((w: any) => {
      const t = w.start ?? w.startTime ?? 0;
      return t >= CHORUS_START;
    }),
  };

  const raw = parseElevenLabsTranscript(filteredTranscript, {
    maxWordsPerLine: 6,
    lineGapThreshold: 0.8,
  });
  const lyrics = shiftLyricsTiming(raw, -CHORUS_START);

  return (
    <LyricsOverlay
      videoSrc={staticFile('videos/<slug>.mp4')}
      lyrics={lyrics}
      style="karaoke"
      fontSize={72}
    />
  );
};

Register in Root.tsx — CRITICAL: use fps={24} to match LTX 2.5 output

// LTX 2.5 Pro generates 24fps. Set fps={24} so Remotion matches natively — no re-encoding needed.
<Composition
  id="Temp_<Slug>"
  component={Temp_<Slug>}
  fps={24}
  durationInFrames={Math.round(<DURATION_SECONDS> * 24)}
  width={1920}
  height={1080}
/>

Register in Root.tsx, render, then cleanup

# Add to Root.tsx (under existing compositions)
cd $REMOTION
npx remotion render Temp_<Slug> out/${SLUG}_lyrics.mp4

# Copy result
cp out/${SLUG}_lyrics.mp4 /Users/aviz/ai-music-video-maker/projects/$SLUG/videos/final.mp4

# Cleanup: remove temp composition + public assets
rm src/compositions/Temp_<Slug>.tsx
rm public/videos/${SLUG}.mp4
rm public/lyrics/${SLUG}.json
# Remove the Composition entry from Root.tsx

Project Structure

projects/<slug>/
├── audio/
│   ├── original.mp3
│   ├── chorus_audio.mp3
│   └── chunks/chunk_01.mp3 ... chunk_N.mp3
├── subtitles/
│   ├── words          (word-level JSON)
│   └── words.srt
├── images/
│   ├── collage.jpg    (4K 3x3)
│   └── angles/
│       ├── angle_1.jpg ... angle_9.jpg
├── videos/
│   ├── clips/shot_01.mp4 ... shot_N.mp4
│   ├── video_only.mp4
│   ├── merged.mp4
│   └── final.mp4      ← FINAL OUTPUT
└── storyboard.md      (Gemini's full analysis + prompts)

Key Principles

Timing: ElevenLabs word timestamps > Gemini timing. Always verify with JSON.

Visuals: Gemini hears the song → Gemini designs the visual identity. Don't use generic prompts.

Variety: Never same angle twice in a row. Rotate: closeup → wide → instrument → crowd → silhouette.

Motion: Every video prompt must include: what moves + how camera moves + lighting event.

Audio: Always mux from original continuous audio (no chunk seams). Fade out 2s.

Dependencies

• yt-dlp — YouTube download
• ffmpeg — audio/video processing
• imagemagick — collage splitting
• ElevenLabs — word-level transcription (transcribe skill)
• Gemini — audio analysis + prompt generation (audio-to-video/scripts/analyze_audio.ts)
• fal.ai LTX 2.5 Pro — video generation (lightricks/ltx-2.5/audio-to-video/pro)
• Remotion — lyrics overlay (~/remotion-assistant)