ACE-Step Lyrics Transcription
Lyrics transcription skill using ACE-Step 1.5 audio model. Dual-backend support (OpenAI Whisper + ElevenLabs Scribe), excellent API key hygiene.
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// RATINGS
Not yet listed on ClawHub or SkillsMP
// README
Table of Contents
- ✨ Features
- ⚡ Quick Start
- 🚀 Launch Scripts
- 📚 Documentation
- 📖 Tutorial
- 🏗️ Architecture
- 🦁 Model Zoo
- 🔬 Benchmark
📝 Abstract
🚀 We present ACE-Step v1.5, a highly efficient open-source music foundation model that brings commercial-grade generation to consumer hardware. On commonly used evaluation metrics, ACE-Step v1.5 achieves quality beyond most commercial music models while remaining extremely fast—under 2 seconds per full song on an A100 and under 10 seconds on an RTX 3090. The model runs locally with less than 4GB of VRAM, and supports lightweight personalization: users can train a LoRA from just a few songs to capture their own style.
🌉 At its core lies a novel hybrid architecture where the Language Model (LM) functions as an omni-capable planner: it transforms simple user queries into comprehensive song blueprints—scaling from short loops to 10-minute compositions—while synthesizing metadata, lyrics, and captions via Chain-of-Thought to guide the Diffusion Transformer (DiT). ⚡ Uniquely, this alignment is achieved through intrinsic reinforcement learning relying solely on the model's internal mechanisms, thereby eliminating the biases inherent in external reward models or human preferences. 🎚️
🔮 Beyond standard synthesis, ACE-Step v1.5 unifies precise stylistic control with versatile editing capabilities—such as cover generation, repainting, and vocal-to-BGM conversion—while maintaining strict adherence to prompts across 50+ languages. This paves the way for powerful tools that seamlessly integrate into the creative workflows of music artists, producers, and content creators. 🎸
✨ Features
⚡ Performance
- ✅ Ultra-Fast Generation — Under 2s per full song on A100, under 10s on RTX 3090 (0.5s to 10s on A100 depending on think mode & diffusion steps)
- ✅ Flexible Duration — Supports 10 seconds to 10 minutes (600s) audio generation
- ✅ Batch Generation — Generate up to 8 songs simultaneously
🎵 Generation Quality
- ✅ Commercial-Grade Output — Quality beyond most commercial music models (between Suno v4.5 and Suno v5)
- ✅ Rich Style Support — 1000+ instruments and styles with fine-grained timbre description
- ✅ Multi-Language Lyrics — Supports 50+ languages with lyrics prompt for structure & style control
🎛️ Versatility & Control
| Feature | Description |
|---|---|
| ✅ Reference Audio Input | Use reference audio to guide generation style |
| ✅ Cover Generation | Create covers from existing audio |
| ✅ Repaint & Edit | Selective local audio editing and regeneration |
| ✅ Track Separation | Separate audio into individual stems |
| ✅ Multi-Track Generation | Add layers like Suno Studio's "Add Layer" feature |
| ✅ Vocal2BGM | Auto-generate accompaniment for vocal tracks |
| ✅ Metadata Control | Control duration, BPM, key/scale, time signature |
| ✅ Simple Mode | Generate full songs from simple descriptions |
| ✅ Query Rewriting | Auto LM expansion of tags and lyrics |
| ✅ Audio Understanding | Extract BPM, key/scale, time signature & caption from audio |
| ✅ LRC Generation | Auto-generate lyric timestamps for generated music |
| ✅ LoRA Training | One-click annotation & training in Gradio. 8 songs, 1 hour on 3090 (12GB VRAM) |
| ✅ Quality Scoring | Automatic quality assessment for generated audio |
🔔 Staying ahead
Star ACE-Step on GitHub and be instantly notified of new releases
🤝 Partners
⚡ Quick Start
Requirements: Python 3.11-3.12, CUDA GPU recommended (also supports MPS / ROCm / Intel XPU / CPU)
Note: ROCm on Windows requires Python 3.12 (AMD officially provides Python 3.12 wheels only)
# 1. Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh # macOS / Linux
# powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex" # Windows
# 2. Clone & install
git clone https://github.com/ACE-Step/ACE-Step-1.5.git
cd ACE-Step-1.5
uv sync
# 3. Launch Gradio UI (models auto-download on first run)
uv run acestep
# Or launch REST API server
uv run acestep-api
Open http://localhost:7860 (Gradio) or http://localhost:8001 (API).
📦 Windows users: A portable package with pre-installed dependencies is available. See Installation Guide.
📦 MacOS users: A portable package with pre-installed dependencies is available. See Installation Guide.
📖 Full installation guide (AMD/ROCm, Intel GPU, CPU, environment variables, command-line options): English | 中文 | 日本語
💡 Which Model Should I Choose?
| Your GPU VRAM | Recommended LM Model | Backend | Notes |
|---|---|---|---|
| ≤6GB | None (DiT only) | — | LM disabled by default; INT8 quantization + full CPU offload |
| 6-8GB | acestep-5Hz-lm-0.6B | pt | Lightweight LM with PyTorch backend |
| 8-16GB | acestep-5Hz-lm-0.6B / 1.7B | vllm | 0.6B for 8-12GB, 1.7B for 12-16GB |
| 16-24GB | acestep-5Hz-lm-1.7B | vllm | 4B available on 20GB+; no offload needed on 20GB+ |
| ≥24GB | acestep-5Hz-lm-4B | vllm | Best quality, all models fit without offload |
The UI automatically selects the best configuration for your GPU. All settings (LM model, backend, offloading, quantization) are tier-aware and pre-configured.
🚀 Launch Scripts
Ready-to-use launch scripts for all platforms with auto environment detection, update checking, and dependency installation.
| Platform | Scripts | Backend |
|---|---|---|
| Windows | start_gradio_ui.bat, start_api_server.bat | CUDA |
| Windows (ROCm) | start_gradio_ui_rocm.bat, `start_api_server_roc |