Human Vocality Primitives
Non-lexical vocal sounds produced under physical load, including strained airflow, exertion exhales, and effort-linked vocal gestures.
Structured at the articulation level using documented production workflows and secured under the Proteus Standard™.
Key technical details for this dataset — including file counts, duration, delivery format, and session context.
Planned technical specifications and recording standards for this dataset.
Total Files:
Total Files (Preview):
Total Duration (Hours):
Sample Rate (Hz):
96000
Bit Depth (Delivery):
24
Dataset Version:
Recording Environment:
Treated Studio
Microphone Configuration:
Performer:
Recording Dates:
Recording Location:
Las Vegas, NV
Produced using standardized capture, editing, and QC protocols with versioned metadata and Proteus-backed provenance.
An overview of what’s included in this dataset — from articulations and performance styles to session context and recording notes.
A structured breakdown of the expressive building blocks in this dataset — including articulations, dynamics, transitions, and any extended techniques captured during recording.
Unlike clip- or phrase-based datasets, this dataset is structured at the articulation and gesture level. This enables interpretable control, expressive variability, and human-aligned modeling, but significantly increases production complexity and significantly limits who can produce such datasets correctly at scale.
A three-layer provenance and integrity framework ensuring verifiable chain-of-custody, tamper-evident delivery, and spectral fingerprinting for enterprise deployment. These layers are versioned and maintained to support long-term auditability, continuity, and enterprise compliance.
All full datasets from HFA include provenance metadata, session identifiers, and spectral integrity markers as part of The Proteus Standard™ for compliant enterprise deployment.
Captured with expert musicians and vocalists across global traditions — ensuring each dataset carries authentic nuance, human expression, and rights-managed provenance.
A three-part listening benchmark: a mixed musical demo built from this dataset, the raw source clip, and an AI model’s attempt to reproduce the same prompt.
A musical demonstration created by replacing a state-of-the-art AI-generated lead instrument with original source recordings from this dataset, then arranged and mastered to preserve musical context. This approach allows direct comparison between current-generation model output and real, rights-cleared acoustic source material.
Directly from the dataset: an isolated, unprocessed example of the source recording.
An unmodified output from a current-gen AI model given the same musical prompt. Included to illustrate where today’s systems still differ from real, recorded sources.
AI model approximations generated using publicly available state-of-the-art music generation systems.
Harmonic Frontier Audio datasets are licensed directly to research teams, startups, and enterprise partners. Access models and terms vary based on use case, scale, and integration needs.
All datasets are delivered with versioned metadata, documented workflows, and Proteus-backed integrity manifests.
We typically respond to inquiries within 1–2 business days.
This dataset is actively being recorded and prepared. You can request early access, previews, or discuss licensing timelines.
We typically respond within 1–2 business days.