StrikerData: Audio Dataset for Speech and Noise Research

StrikerData is an audio dataset containing human speech, environmental noise, and other sound types. It was developed by Strikersoft for research and development in audio and speech technologies. The dataset was last updated on January 22, —.

Use Cases

• Training speech recognition models based on clean and distorted human speech.
• Developing noise classification or filtering systems based on human-made and non-human noise categories.
• Benchmarking audio source separation algorithms based on the mixture of speech and environmental sounds.
• Augmenting audio datasets for machine learning based on the provided sound type percentages.

Strengths

• Contains a defined mix of sound types: 20% clean human speech, 15% distorted speech, 15% human-made noise, and 50% non-human noise.
• Explicitly developed for research and development in audio and speech technologies.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file size are unknown, which may limit suitability assessment.

Provenance

Source

Strikersoft

Collection Method

Developed by Strikersoft; specific collection method is not described.

Time Range

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Freshness

Last updated 2026-01 22 00:51:26; freshness should be verified.

Geography

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