metadata

pretty_name: Procedural Engine Sounds Dataset
task_categories:
  - audio-to-audio
  - audio-classification
  - automatic-speech-recognition
tags:
  - audio
  - audio-dataset
  - engine-sounds
  - combustion-engine
  - procedural-generation
  - time-aligned
  - rpm
  - torque
  - automotive
  - nvh
  - vehicle-acoustics
  - sound-synthesis
  - noise-free
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
Version: 1.0
Publication Year: 2025
Point of Contact: [email protected]
License: CC BY-NC 4.0

Research Applications

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 suppression or other related tasks

Technical Specifications

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 in WAV format.

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

File Organization

README.txt (this file)
USAGE.txt (quick start guide)
audio/
├── A_full_set/ (767 files, ~2.46 hours, ~3.16 GB)
├── B_full_set/ (767 files, ~2.46 hours, ~3.16 GB)
├── C_full_set/ (767 files, ~2.46 hours, ~3.16 GB)
├── D_full_set/ (767 files, ~2.46 hours, ~3.16 GB)
├── E_large_set/ (717 files, ~2.30 hours, ~2.96 GB)
├── F_large_set/ (717 files, ~2.30 hours, ~2.96 GB)
├── G_large_set/ (717 files, ~2.30 hours, ~2.96 GB)
└── H_large_set/ (717 files, ~2.30 hours, ~2.96 GB)
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)

File Formats

Audio Files:

Format: WAV
Sample Rate: 48 kHz
Channels: 4 (quad-channel)
Bit Depth: 16 bit

Metadata Files:

Summary files: JSON format
Statistics files: CSV format (comma-separated values)

Data Structure

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 Access

Each audio file is a standard WAV file containing a 4-channel audio array at 48 kHz sample rate. When loaded, you receive the raw multichannel audio data from which RPM and torque information can be extracted from channels 3 and 4 respectively.

Audio Signal Encoding

RPM Signal: Channel 3 contains engine speed values in RPM scaled by 0.0001 (multiply by 10,000 to get actual RPM)
Torque Signal: Channel 4 contains torque values in Newton meters scaled by 0.001 (multiply by 1,000 to get actual Nm)
Engine Audio: Channels 1-2 contain the stereo procedural engine sound

Technical Requirements

To work with this dataset, you will need:

Audio processing software capable of reading multi-channel WAV files
Programming languages: Python (recommended with librosa, soundfile, or scipy), MATLAB, R, or similar
For metadata: JSON and CSV reading capabilities

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 verify representativeness 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

License and Usage

License

This dataset is released under CC BY-NC 4.0 license (Creative Commons Attribution-NonCommercial 4.0 International).

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

Citation

@dataset{doerfler_2025_procedural_engine_sounds,
  author       = {Doerfler, Robin},
  title        = {Procedural Engine Sounds Dataset},
  month        = {August},
  year         = 2025,
  publisher    = {Zenodo},
  version      = {1.0},
  doi          = {10.5281/zenodo.16883336},
  url          = {https://doi.org/10.5281/zenodo.16883336}
}

Contact Information

For questions, issues, or collaboration opportunities:

Email: [email protected]
Dataset DOI: 10.5281/zenodo.16883336
Related Publications: Available upon paper publication

Acknowledgments

This dataset was created through procedural audio synthesis leveraging established principles from engine acoustics research, including engine order analysis, extended harmonic-plus-noise synthesis methodologies, and exhaust system resonance modeling. The synthesis methodology builds upon decades of foundational research in vehicle acoustics and internal combustion engine sound modeling. Special thanks to the digital signal processing and vehicle acoustics research communities for their foundational work that made this dataset possible.