metadata
license: other
gated: manual
task_categories:
- audio-classification
tags:
- audio
- sfx
- sound-effects
- krampfstadt-studio
- commercial
Krampfstadt Studio - Global SFX Audio Dataset
⚠️ Commercial Dataset — Purchase & Authorization Required
This is a premium sound effects (SFX) library owned and distributed by Krampfstadt Studio. Access to the raw audio files and dataset splits is restricted exclusively to authorized buyers.
🛒 How to Purchase & Gain Access
- Buy an AI/ML License: Purchase the appropriate commercial license directly on our official website: www.krampfstadtstudio.com.
- Request Access: Click the "Request Access" button at the top of this Hugging Face page.
- Verify Your Purchase: In the access request form, enter your Invoice/Order Number or the Email Address used during checkout on our site.
- Approval: Once your order is verified, access will be granted to your Hugging Face account (typically within a few hours).
🔊 Dataset Overview
This dataset offers comprehensive global coverage of professional sound effects across 350+ categorized sound libraries, featuring over 53,000 high-quality audio files.
- Total FX Libraries: 350+
- Total Audio Clips: 53,000+
- Format: Uncompressed WAV / Lossless Audio
- Use Cases: Generative audio model training, speech & acoustic classification, game development, and film post-production.
📜 Terms of Use & Licensing
- License Type: Custom Proprietary / Commercial License (
license: other). - Commercial Usage: Permitted only upon valid license purchase from Krampfstadt Studio.
- Redistribution: Re-selling, re-distributing, public sharing, or sub-licensing of raw audio files is strictly prohibited.
- Model Training: Commercial training of AI/ML models is permitted strictly under our AI/ML licensing terms.
💻 How to Load the Dataset (After Approval)
Once your request is approved, you can load the dataset using the Hugging Face datasets library with your access token:
from datasets import load_dataset
dataset = load_dataset(
"your-hf-username/your-dataset-name",
token="YOUR_HF_TOKEN"
)
# Access first sample
print(dataset["train"][0])