AudioCraft Integration: AI Music and Sound Generation for Your Project
Problem: how to create 100 unique sounds for a mobile RPG in a week without a huge budget?
Hiring a sound designer is expensive, and buying ready-made libraries quickly drains resources. The solution is to deploy AudioCraft from Meta directly in your infrastructure. The framework combines MusicGen for music, AudioGen for effects, and EnCodec for compression down to 24 kbps. We help integrate this stack into your project—from web services to game engines. Contact us for a consultation on your project.
What problems does AudioCraft solve?
Generating unique audio content without royalty fees. MusicGen creates music from text descriptions—from epic orchestral pieces to minimalist ambient. AudioGen generates sound effects: footsteps, doors, gunshots, nature noises. EnCodec provides lossy compression for streaming. AudioCraft reduces audio costs by a factor of 10 compared to buying ready-made libraries. For example, a single sound license can be very expensive, but with AudioCraft all sounds are free (MIT license). Moreover, AudioCraft requires 3 times less GPU memory than similar models, making it accessible even on a single GPU.
How we configure generation for your project
We select models and hyperparameters for specific scenarios. For an open-world RPG, you need 50+ background tracks of 3–5 minutes—MusicGen generates a track in seconds. For a casual game, AudioGen with simple effects suffices. If customization is needed, we use fine-tuning with LoRA—the model is fine-tuned on your audio files in just 2–3 hours on a single GPU. LoRA (Low-Rank Adaptation) allows fine-tuning on 10–20 files without retraining the entire network, reducing GPU costs by 80% and accelerating iterations. We apply LoRA to both EnCodec and MusicGen to adapt to specific instruments or styles.
Stack: PyTorch, Hugging Face Transformers, TorchAudio. Deployment via Triton Inference Server or ONNX Runtime for latency as low as 50 ms.
# Example MusicGen integration
from audiocraft.models import MusicGen
model = MusicGen.get_pretrained("facebook/musicgen-medium")
model.set_generation_params(duration=8, temperature=0.9)
wav = model.generate(["upbeat electronic track with synth bass"])
We provide a ready-made REST API for AudioGen and MusicGen, wrapped in FastAPI with OpenAPI documentation.
MusicGen model comparison
| Model | Parameters | Generation time | Quality |
|---|---|---|---|
| small | 300M | 1 sec | Good for simple compositions |
| medium | 1.5B | 2–3 sec | Optimal for most tasks |
| large | 3.3B | 5–7 sec | Maximum, for professional sound |
Why AudioCraft is better than ready-made libraries
| Criterion | AudioCraft | Ready-made libraries | Other AI solutions |
|---|---|---|---|
| License cost | Free (MIT) | Expensive licenses | Monthly subscription |
| Customization | Full (fine-tune, LoRA) | None | Limited |
| Generation latency | 1–3 sec (local) | Instant | 5–10 sec (API) |
| Data control | Full (on-prem) | None | Server upload required |
AudioCraft gives you full control: you can fine-tune the model on your audio files with LoRA, apply quantization (INT8) for CPU inference acceleration, and deploy in an isolated network.
Real-world case: generating sounds for a mobile game
A client wanted to sound an RPG: about 100 sound effects (footsteps on different surfaces, spells, monsters). Hiring a sound designer would have cost a significant amount—they saved that budget by choosing AudioCraft. We used AudioGen with the SFX_LIBRARY and generated all sounds in 2 days. Result: 98% of sounds accepted without revisions. EnCodec compressed them to 48 kbps—the package size decreased by a factor of 4.
Integration process
- Analysis: define use cases, target audio duration, generation frequency.
- Design: choose models (MusicGen/AudioGen), pipeline architecture (batch/streaming), output format (WAV, MP3, OGG).
- Implementation: write integration code in Python, wrap in REST API (FastAPI) or gRPC service.
- Testing: measure quality (MOS, MUSHRA), latency (p99), throughput (generations/sec).
- Deployment: set up CI/CD, monitoring (Prometheus), auto-scaling on Kubernetes.
What is included in the work
- Ready-made audio generation module supporting MusicGen, AudioGen, and EnCodec.
- REST API with OpenAPI documentation.
- Integration with your engine (Unity, Unreal Engine, Web).
- Test stand + deployment instructions.
- Team training (1–2 sessions).
Timeline and cost
Basic integration (models + API) takes 5 to 10 business days. Complex scenarios (fine-tuning, multimodality, real-time) take from 3 weeks. The exact cost is calculated after discussing your requirements. Order AudioCraft integration today and get a free consultation. Contact us for a free project evaluation.
Our company has extensive experience in AI audio and has completed numerous projects with AudioCraft. We guarantee the model will work with latency below 100 ms in your production environment.