Isolated Guitar Chord Recordings For Real-World Audio Classification

Isolated guitar chord recordings are designed for audio classification tasks like chord recognition and real-time music analysis. The dataset was recorded on a Fender FA-15 3/4 acoustic guitar in realistic acoustic conditions, including minor background sounds, to improve inference robustness. The author is rodriler, with a last recorded update in February 2026.

Use Cases

• Train a chord recognition model on isolated guitar chord recordings to classify chord types.
• Analyze the impact of realistic acoustic conditions and background sounds on audio classification model performance.
• Develop real-time music analysis systems using recordings from a Fender FA-15 3/4 acoustic guitar.

Strengths

• Recordings are intentionally captured in realistic acoustic conditions to improve robustness for real-world inference.
• Data includes minor background sounds, simulating non-studio environments for more practical model training.
• Specific recording instrument is documented: a Fender FA-15 3/4 acoustic guitar.

Limitations

• Core quantitative metadata like row count, column definitions, and file size are unknown.
• The dataset's scope is limited to a single instrument model, which may not generalize to other guitars or recording setups.
• License information is unavailable, which restricts clarity on permissible use cases.

Provenance

Source

Hugging Face dataset by author rodriler.

Collection Method

Manual recording on a specified acoustic guitar.

Time Range

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Freshness

Last updated February 2026.

Geography

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