strikersoft/strikerData
🎧 StrikerData Overview StrikerData is an audio dataset developed by Strikersoft for research and development in audio and speech technologies.It contains human speech, environmental noise, and other sound types. The dataset is available for non-commercial use only, except for the company Strikersoft. Category Percentage of Total Dataset Clean human speech 20% Distorted speech 15% Human-made noise 15% Non-human noise 50% ⚖️… See the full description on the dataset page: https://huggingface.co/datasets/strikersoft/strikerData.
🎧 StrikerData
Overview
StrikerData is an audio dataset developed by Strikersoft for research and development in audio and speech technologies. It contains human speech, environmental noise, and other sound types. The dataset is available for non-commercial use only, except for the company Strikersoft.
⚖️ License
This dataset is released under a Custom License.
Geographic Restrictions
Access to this dataset is strictly prohibited for individuals or entities located in or associated with the following countries:
- Russia
- Belarus
- Iran
- North Korea
Commercial Use Restrictions
The dataset is licensed for non-commercial use only, except for Strikersoft. No other individual or entity may use this dataset for commercial purposes without the explicit written consent of Strikersoft.
License Termination
Strikersoft reserves the right to revoke access at any time if:
- The dataset is used commercially without permission.
- Access occurs from restricted regions listed above.
Legal Jurisdiction
This license agreement is governed by the laws of the European Union (EU). Any disputes will be resolved under the jurisdiction of Strikersoft’s legal entity.
🧠 How to Use
To use this dataset, you must:
- Agree to the Custom License above.
- Confirm you are not located in or associated with a restricted country.
- Use the dataset for non-commercial purposes only (unless you are Strikersoft).
Example (Python)
from datasets import load_dataset
dataset = load_dataset("bonchardon/strikerData", split="train", streaming=True)
sample = next(iter(dataset))
print(sample)
