Harmonic-Frontier-Audio/NonLexical_Vocal_Gestures_Preview

Harmonic Frontier Audio – Non-Lexical Vocal Gestures (Preview, v0.9)

A high-fidelity human vocal dataset designed for AI training, speech research, and expressive voice modeling.

Non-Lexical Vocal Gestures (Preview), created by Harmonic Frontier Audio, provides a compact reference set demonstrating the quality, formatting, and metadata conventions used in the Harmonic Frontier Audio Human Vocality Primitives series.

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🔎 Summary

This dataset provides high-quality, rights-cleared recordings of speech-like non-lexical vocal gestures — brief and sustained human vocal behaviors that carry conversational or affective information without forming full words.

The full dataset encompasses:

• low- and mid-register neutral closed-mouth hums with stable pitch centers and nasal resonance
• soft contented or affirmative “hmm” gestures with relaxed airflow
• disapproving alveolar “tsk” clicks with narrow high-frequency transients
• short playful yelps with rapid onsets and elevated pitch
• low-register frustration groans with gradual pitch movement and increased laryngeal tension
• sustained uncertain “uh” gestures with minimal articulation change
• reluctant voiced-to-breathy exhalation transitions

These characteristics make the dataset valuable for AI speech and voice modeling, conversational-agent synthesis, non-verbal communication modeling, phonetics research, expressive audio generation, affective interaction systems, and human-aligned vocal control systems.

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/non-lexical-vocal-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 Non-Lexical Vocal Gestures

Non-lexical vocal gestures are speech-adjacent human sounds that function outside conventional word formation. They can communicate conversational stance, hesitation, affirmation, reluctance, frustration, playfulness, or other subtle interpersonal cues through changes in phonation, airflow, pitch, resonance, and articulation.

This dataset spans both sustained vocal behaviors and brief transient gestures, including neutral hums, affirmative “hmm” sounds, alveolar clicks, yelps, groans, uncertain vowel-like gestures, and voiced-to-breathy exhalation transitions. Recordings were produced naturally and conversationally without full emotional acting.

These phenomena are foundational to:

• conversational and expressive voice synthesis
• non-verbal human communication modeling
• speech-adjacent gesture classification
• affective and socially aware AI systems
• phonetic study of non-lexical vocal behavior
• multimodal and embodied agent interaction

This dataset presents a natural, non-linguistic, speech-like representation of non-lexical vocal behavior.
It is not designed as acted dialogue or semantic speech, but rather to isolate acoustic primitives underlying common conversational and affective vocal gestures.

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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 consistency
• No compression, normalization, or creative processing applied
• High-pass filtered at ~40 Hz to remove subsonic rumble

This preview includes 2 representative audio files, selected to demonstrate:

• a contented “hmm” gesture — soft affirmative non-lexical voicing with light phonation and relaxed airflow
• an uncertain “uh” gesture — sustained neutral vowel-like voicing with minimal articulation change

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Metadata (.csv)

Includes structured fields for:

• file name
• sound source type
• airflow type
• phonation type
• gesture and articulation descriptors
• microphone and recording chain
• sample rate, bit depth, and dataset version

Metadata follows the Harmonic Frontier Audio – Foundations schema.

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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
• Captured at 96 kHz / 32-bit float, rendered as 96 kHz / 24-bit mono WAV for release.
• Performer positioned approximately 3.5 inches from the microphone, with the microphone approximately 10–15 degrees off-axis.
• Burst gestures were recorded at approximately 1–2 seconds, with sustained gestures approximately 4–7 seconds.
• Performances were kept natural and conversational, with full words avoided and mouth/posture reset between takes.
• Consistent microphone distance was maintained across conditions.

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🌈 Spectrogram Preview

Below is a spectrogram illustrating the sustained harmonic structure, resonance characteristics, and subtle phonatory differences characteristic of contented “hmm” and uncertain vowel-like non-lexical vocal gestures:

⚡ Usage

This preview pack is designed for:

• Evaluation of Harmonic Frontier Audio dataset quality and structure
• Testing AI and DSP systems that model non-lexical conversational and affective vocal gestures
• Research in phonetics, expressive voice synthesis, conversational AI, and non-verbal communication
• Creative and technical applications requiring natural hums, clicks, yelps, groans, hesitation sounds, and related speech-adjacent vocal primitives

👉 Note: This is not a full dataset.
The complete Non-Lexical Vocal Gestures dataset includes low- and mid-register neutral hums, contented “hmm” gestures, disapproving “tsk” clicks, playful yelps, frustration groans, uncertain “uh” gestures, and reluctant voiced-to-breathy exhalation transitions, and is available for licensing.

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💡 Full Dataset Availability

This is a preview pack of the Non-Lexical Vocal Gestures Dataset.
The complete dataset is available for commercial 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/Non_Lexical_Vocal_Gestures_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

• Human Vocality Primitives Series (Previews)
• Celtic Constellation Series (Previews)
• Extended Vocal Techniques Spectrum (Previews)
• Novelty Gems Cabinet (Previews)

(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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🗒️ Release Notes

Version 0.9 (March 2026) – Initial Preview Pack release for Non-Lexical Vocal Gestures.
See CHANGELOG.md for detailed version history.

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Citation

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

Pullen, B. (2026). Non-Lexical Vocal Gestures Dataset (Preview) [Data set]. Harmonic Frontier Audio. Zenodo. https://doi.org/10.5281/zenodo.21990092

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

BibTeX

@dataset{pullen_2026_nonlexicalvocalgestures_preview,
  author       = {Blake Pullen},
  title        = {Non-Lexical Vocal Gestures Dataset (Preview)},
  year         = {2026},
  publisher    = {Harmonic Frontier Audio},
  version      = {0.9},
  doi          = {10.5281/zenodo.21990092},
  url          = {https://doi.org/10.5281/zenodo.21990092}
}