metadata

pretty_name: Procedural Engine Sounds Dataset
task_categories:
  - audio-to-audio
  - audio-classification
  - automatic-speech-recognition
tags:
  - audio
  - synthetic
  - engine-sounds
  - procedural-generation
  - automotive
  - sound-synthesis
  - mechanical-sounds
  - audio-analysis
  - vehicle-acoustics
size_categories:
  - 10B<n<100B
license: cc-by-nc-4.0

Procedural Engine Sounds Dataset

Dataset Description

The Procedural Engine Sounds Dataset is a comprehensive collection of synthetically generated and annotated engine audio samples. This dataset contains procedurally generated high-resolution engine sounds free of confounding noises, with detailed time-aligned annotations, designed for research in audio processing, vehicle acoustics, and synthetic sound generation.

Dataset Details

Dataset Summary

Repository: procedural-engine-sounds
Paper: [Coming Soon]
Point of Contact: [email protected]

Supported Tasks

Audio Generation: Train models to generate realistic engine sounds conditioned to time-varying engine operation states
Audio Classification: Predict RPM and Engine Torque based on audio signals
Audio Analysis: Research vehicle acoustics and engine sound patterns
Sound Synthesis: Develop procedural audio generation techniques
Data Augmentation: Use as augmentation material for in-cabin speech detection and recognition, noise supression or other related tasks

Languages

This dataset contains only audio signals - no textual or linguistic content. Both the engine sounds and annotations (RPM/torque information) are provided as audio signals at 48 kHz sample rate.

Dataset Structure

Data Organization

The dataset is organized into 8 distinct sets with two categories:

Full Sets (A, B, C, D):

3,068 files total (across 4 sets)
~9.83 hours of audio total
~12.65 GB total
Per set (average): ~767 files, ~2.46 hours, ~3.16 GB

Large Sets (E, F, G, H):

2,867 files total (across 4 sets)
~9.18 hours of audio total
~11.82 GB total
Per set (average): ~717 files, ~2.30 hours, ~2.96 GB

Dataset Total: 5,935 files, ~19.01 hours, ~24.47 GB

dataset/
├── audio/
│   ├── A_full_set/
│   ├── B_full_set/
│   ├── C_full_set/
│   ├── D_full_set/
│   ├── E_large_set/
│   ├── F_large_set/
│   ├── G_large_set/
│   └── H_large_set/
└── metadata/
    ├── A_full_set_summary.json
    ├── A_full_set_stats.csv
    ├── B_full_set_summary.json
    ├── B_full_set_stats.csv
    └── … (16 metadata files total)

Data Instances

Each audio file contains 4-channel audio at 48 kHz sample rate:

Channel 1-2: Stereo engine sound audio
Channel 3: Engine speed (RPM × 0.0001) as continuous audio signal
Channel 4: Engine torque (Nm × 0.001) as continuous audio signal

Metadata Structure

Summary Files (.json)

Per-set statistics including:

num_files: Number of audio files in set
total_duration_*: Duration in seconds/minutes/hours
total_size_gb: Storage size in GB
rpm_distribution: Statistical distribution (min, max, mean, std, percentiles)
torque_distribution: Statistical distribution (min, max, mean, std, percentiles)

Statistics Files (.csv)

Per-file metrics with columns:

filename: Audio file name
samplerate: Sample rate (48 kHz)
duration_sec: File duration in seconds
size_MB: File size in megabytes
rpm_min/max/mean/std: RPM statistics for the file
torque_min/max/mean/std: Torque statistics for the file

Data Fields

When loaded programmatically:

audio: 4-channel audio array [channels, samples]
sample_rate: 48000 Hz
filename: Original audio filename
duration: Audio length in seconds
rpm_range: [min, max] RPM values from channel 3
torque_range: [min, max] torque values from channel 4

Audio Signal Encoding

RPM Signal: Channel 3 contains engine speed values in RPM scaled by 0.0001 (multiply by 10000 to get actual RPM)
Torque Signal: Channel 4 contains torque values in Newton meters scaled by 0.001 (multiply by 1000 to get actual Nm)
Engine Audio: Channels 1-2 contain the stereo procedural engine sound

Dataset Creation

Source Data

All audio samples are synthetically generated using procedural audio synthesis techniques. No real-world engine recordings were used for audio generation. Dataset results were thoroughly analysed and compared to real world recordings to varify representiveness and similarity regarding engine order magnitudes and harmonic deviations.

Annotations

Annotations were created during the generation process, with additional manual verification for quality assurance.

Considerations for Using the Data

Social Impact of Dataset

This dataset enables research in:

Automotive audio simulation
Vehicle sound design
Audio processing algorithms
Synthetic data generation techniques

Discussion of Biases

As a synthetic dataset, it reflects the biases inherent in the procedural generation algorithms and may not capture all real-world engine sound variations.

Other Known Limitations

Limited to procedurally generated sounds
May not represent all engine types or acoustic environments
Generated with empirically determined synthesis parameters, hence contains fictional engine types and exhaust pipe configurations

Additional Information

License

This dataset is released under CC BY-NC 4.0 license.

Attribution Required: Please cite this dataset in any research or publications.

Citation

@dataset{procedural_engine_sounds,
  title={Procedural Engine Sounds Dataset},
  author={Robin Doerfler},
  year={2025},
  url={https://huggingface.co/datasets/rdoerfler/procedural-engine-sounds},
  license={CC-BY-NC-4.0}
}