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title: Harmonic Frontier Audio
emoji: 🎧
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colorTo: indigo

Harmonic Frontier Audio

Harmonic Frontier Audio (HFA) produces rights-cleared, provenance-audited audio datasets designed for teams building the next generation of music, audio, voice, and multimodal AI systems.

Our catalog focuses on rare, traditional, and hard-to-source instruments and vocal techniques, recorded and structured at the articulation and gesture level rather than as loosely labeled clips or phrases. This enables interpretable modeling, expressive control, and defensible downstream use.

All datasets are created using documented production workflows and are governed by the Proteus Standard™ — a provenance and integrity framework designed to support compliant AI training, long-term auditability, and enterprise deployment.
Learn more about the Proteus Standard → https://harmonicfrontieraudio.com/proteus-standard

Harmonic Frontier Audio is founded and operated by Blake Pullen, a musician, recording engineer, and creative technologist with a background spanning traditional music performance, audio production, and technical systems design.

What we provide

  • High-fidelity, professionally recorded acoustic source material
  • Articulation-level and gesture-aware dataset structure
  • Detailed technical metadata and session documentation
  • Rights-cleared licensing suitable for research and commercial use
  • Preview releases on Hugging Face for evaluation and discoverability
  • Full datasets licensed directly through Harmonic Frontier Audio

Current releases & roadmap

Preview datasets currently available include:

  • Scottish Smallpipes in A (preview subset)
  • Highland Bagpipes (preview subset)
  • Irish Tin Whistle (D) (preview subset)
  • Kalimba (preview subset)
  • Kazoo (preview subset)
  • Overtone Singing (preview subset)
  • Subharmonic Phonation / Vocal Fry (preview subset)

Planned expansion spans additional Celtic instruments, global folk traditions, world percussion, human vocality primitives, and extended vocal techniques, with multiple dataset families structured under a consistent technical framework.

More information

Citation

If you use Harmonic Frontier Audio datasets in academic or applied work, please cite the specific dataset(s) you used.

Each dataset repository includes a DOI and BibTeX entry in its README.

For a general reference to the project:

Harmonic Frontier Audio (2025).
Rights-cleared acoustic datasets for music and audio machine learning.
Available at: https://huggingface.co/Harmonic-Frontier-Audio

BibTeX

@misc{harmonicfrontieraudio2025,
  author       = {Harmonic Frontier Audio},
  title        = {Rights-cleared acoustic datasets for music and audio machine learning},
  year         = {2025},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/Harmonic-Frontier-Audio}},
  note         = {General reference for the Harmonic Frontier Audio catalog. Please also cite specific dataset DOIs as listed in each dataset README.}
}

Contact & collaboration

Harmonic Frontier Audio collaborates with researchers, startups, and enterprise teams working in music AI, audio ML, and related fields.