Harmonic-Frontier-Audio/Overtone_Singing_Preview

Harmonic Frontier Audio – Overtone Singing (Preview, v0.9)

A high-fidelity vocal dataset designed for AI training, music research, and creative sound development.

Overtone Singing (Preview), created by Harmonic Frontier Audio, provides a compact reference set demonstrating the quality, formatting, and metadata conventions used in the Harmonic Frontier Audio Extended Vocal Techniques Spectrum.

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🔎 Summary

This dataset provides high-quality, rights-cleared recordings of Overtone Singing — an extended vocal technique in which harmonic partials are selectively amplified above a sustained fundamental through precise vocal tract shaping.
The recordings emphasize harmonic isolation, spectral clarity, and controlled overtone movement, making them valuable for AI voice modeling, spectral analysis, harmonic synthesis, and human-aligned vocal control research.

Developed by Harmonic Frontier Audio, this preview follows The Proteus Standard™ for dataset provenance, transparency, and ethical AI use.
Learn more about the Proteus Standard → https://harmonicfrontieraudio.com/proteus-standard

Full dataset details and licensing information are available at: https://harmonicfrontieraudio.com/datasets/overtone-singing

It offers clean, consistent audio files capturing overtone singing across stable fundamentals, moving harmonic trajectories, vowel-modulated resonances, and controlled expressive gestures.

If you find this dataset useful, please consider giving it a 🤍 on Hugging Face to help others discover it.

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🎶 About Overtone Singing

Overtone singing is one of the world’s most striking and acoustically fascinating vocal arts.
Practitioners manipulate the shape of the vocal tract to filter and emphasize individual harmonics, creating the illusion of multiple pitches from a single voice.

While it is best known from Tuvan and Mongolian traditions (such as Khoomei, Sygyt, and Kargyraa), variations of overtone singing appear across many cultures — including Tibetan chant, Sardinian cantu a tenore, and modern Western choirs.

This dataset presents a neutral, non-traditional representation of overtone singing.
It is designed not to imitate any specific cultural style but to serve as a technical and expressive study of harmonic isolation and control — useful for both acoustic analysis and generative modeling of the human voice.

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📂 Contents

Audio Files (.wav)

• Recorded at 96 kHz / 24-bit WAV format
• Exported as mono
• Fade-ins and fade-outs of 3–5 ms applied for transient consistency
• DC offset minimized and normalized to maintain consistent loudness
• No compression, normalization, or external processing applied
• High-pass filtered at ~40 Hz to remove subsonic rumble

Categories in this Preview

1. Sustained Fundamentals
   • Long tones on single fundamentals with isolated harmonics
2. Harmonic Intervals
   • Alternation between two harmonics within a sustained fundamental
3. Arpeggio Gestures
   • Sequential harmonic articulations forming triadic or scalar structures
4. Glissando
   • Continuous overtone sweeps across the harmonic series
5. Short Melodic Exercise
   • Simple original melody emphasizing controlled harmonic shifts and transitions

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Metadata (.csv)
Includes structured fields for file name, category, content, fundamental pitch, harmonic numbers and pitches, microphone, channel configuration, sample rate, bit depth, recording chain, and dataset version.

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🎤 Recording Notes

• Recorded in a treated studio environment using a single-mic setup:
  • Microphone: Rode NT1-A condenser microphone
  • Recording chain: Rode NT1-A → Zoom F8n Pro
• Recorded at 96 kHz / 32-bit float, rendered as 96 kHz / 24-bit mono WAV for release.
• Room tone and subtle breath noise were preserved to retain the natural acoustic realism of overtone production.

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🌈 Spectrogram Preview

Below is a spectrogram showing the clear separation of harmonic peaks above the sustained fundamental pitch, characteristic of overtone singing:

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🎧 Demonstration Audio

This repository includes three audio examples for listening and comparison:

1. Dataset in musical context (mixed & mastered)
A brief musical excerpt demonstrating the Overtone Singing dataset integrated into a musical arrangement, highlighting expressive timbre and real-world usability.

Track: “Overtone Singing Example”
Producer: Blake Pullen
Source Audio: Harmonic Frontier Audio – Overtone Singing (Preview)

2. Raw dataset recording
An unprocessed audio excerpt taken directly from the dataset’s audio files, representing the actual licensed source material without musical context or processing.

3. AI-generated melodic proxy (overtone singing not represented)
A fully AI-generated reference track created without using any Harmonic Frontier Audio recordings.
Because current generative music models do not support spectral melody or overtone-based pitch structures, this example uses a conventional high-pitched melodic instrument as a proxy, illustrating the limitations of existing systems when attempting to approximate overtone singing.

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📜 Demo & Licensing Note

The Demos/ folder contains demonstration material only.
Only the raw recordings in the dataset audio files constitute the licensed dataset.
AI-generated reference tracks are not part of the dataset and are not licensed for training or reuse.

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🪶 Production Notes

• Instrumental accompaniment in the contextual demo was generated using Suno (Pro plan) under a commercial license.
• A dataset recordings were performed, recorded, and produced by Blake Pullen for Harmonic Frontier Audio.

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⚡ Usage

This preview pack is designed for:

• Evaluation of Harmonic Frontier Audio dataset structure and fidelity
• Testing AI and DSP systems that model or classify harmonic timbres
• Creative sound design and extended voice synthesis research

👉 Note: This is not a full dataset.
The complete Harmonic Frontier Audio dataset for Overtone Singing will include:

• Expanded harmonic and vowel variations
• Dynamic overtone transitions and melodic gestures
• Additional tuning modes and glissando articulations

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💡 Full Dataset Availability

This is a preview pack of the Overtone Singing Dataset.
The complete dataset — with extended harmonic content and melodic variation — will be available for licensing.

For licensing inquiries:
📩 info@harmonicfrontieraudio.com

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📥 How to Use This Dataset in Python

You can load the Parquet-converted version of this dataset directly with the datasets library:

from datasets import load_dataset

dataset = load_dataset(
    "Harmonic-Frontier-Audio/Overtone_Singing_Preview",
    split="train"
)

print(dataset)

⚙️ Note: Parquet conversion and load_dataset() support will be available within 2–3 days of publication.

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🔗 Explore More from Harmonic Frontier Audio

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

(All datasets follow The Proteus Standard™ for ethical dataset provenance and licensing.)

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📜 License

Released under CC BY-NC 4.0.

• Free for non-commercial use, testing, and research.
• Commercial licensing available via Harmonic Frontier Audio.
• A formal rights declaration is included in this dataset bundle.

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📧 Contact

Harmonic Frontier Audio
📩 info@harmonicfrontieraudio.com
🌐 https://harmonicfrontieraudio.com/

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🔮 Future Roadmap

This preview release is part of the Harmonic Frontier Audio – Extended Vocal Techniques Spectrum.
Upcoming planned datasets include:

• Whisper Phonation
• Falsetto
• Vocal Percussion
• Growl / Metal Vocals
• Subharmonic Phonation / Vocal Fry (Full Dataset)

Over time, Harmonic Frontier Audio will expand the Extended Vocal Techniques Spectrum alongside its Folk & World Instrument catalogs — creating the first unified library of ethical, rights-cleared world and human vocal datasets for AI training, synthesis, and sound design.

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🗒️ Release Notes

Version 0.9 (Nov. 2025) – Initial Preview Pack release for Overtone Singing.
See CHANGELOG.md for detailed version history.

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Citation

If you use this dataset in your research, please cite:

Pullen, B. (2025). Overtone Singing Dataset (Preview) [Data set]. Harmonic Frontier Audio. Zenodo.
https://doi.org/10.5281/zenodo.17812972

ORCID: https://orcid.org/0009-0003-4527-0178

BibTeX

@dataset{pullen_2025_overtone_preview,
  author       = {Blake Pullen},
  title        = {Overtone Singing Dataset (Preview)},
  year         = {2025},
  publisher    = {Harmonic Frontier Audio},
  version      = {0.9},
  doi          = {10.5281/zenodo.17812972},
  url          = {https://doi.org/10.5281/zenodo.17812972}
}