Ambient Noise Audio Collection for ASR Model Improvement

An audio dataset collected by Willy030125 and last updated on 2025-08-19. It aggregates ambient noise recordings from sources including Kaggle datasets on hospital and general ambient noise. The primary purpose is to reduce hallucinations in Automatic Speech Recognition models like Whisper.

Use Cases

• Fine-tuning ASR models to reduce hallucinations based on the described collection of non-speech audio.
• Creating background noise filters for audio processing pipelines based on the ambient noise samples.
• Benchmarking ASR model robustness against environmental audio based on the described use case.
• Augmenting speech datasets with realistic noise for training based on the dataset's stated purpose.

Strengths

• Dataset has a clear, targeted purpose for improving ASR model performance on non-speech audio.
• Last update timestamp is explicitly provided: 2025-08-19 09:52:31.
• Sources are referenced, indicating a curated collection from existing Kaggle datasets.

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, file formats, and license information are unknown, which may limit suitability assessment.

Provenance

Source

Aggregated from Kaggle datasets (hospital-ambient-noise, ambient-noise) by author Willy030125.

Collection Method

Collected from existing open data sources.

Time Range

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Freshness

Last updated 2025-08-19 09:52:31; freshness should be verified.

Geography

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