Deepfake Audio Dataset for Real vs Fake Speech Detection

A speech dataset designed for deepfake audio detection, containing both real and fake audio samples. The dataset was sourced from Kaggle, but the author, organization, and specific collection details are unknown. The total size, number of samples, and last update date are not provided.

Use Cases

• Train binary classifiers to distinguish real from fake speech based on audio features.
• Benchmark detection algorithms for synthetic or manipulated audio.
• Analyze acoustic artifacts and patterns indicative of audio deepfakes.

Strengths

• Dataset is explicitly designed for the specific task of deepfake audio detection.
• Contains a curated comparison of real and fake speech samples.

Limitations

• Row count and total dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect temporal or source bias inherent to its collection on Kaggle.

Provenance

Source

Kaggle

Collection Method

Collection method is not described.

Time Range

Temporal coverage is unknown.

Freshness

Last update date is unknown; freshness unverified.

Geography

Spatial coverage is unknown.