AIAPS-001 — Core Specification

Public Draft

AIAPS Specification v1.0

Public Draft — 2026

AIAPS defines a protection and verification standard for audio recordings designated as prohibited for unauthorized AI training, dataset ingestion, voice cloning, style modeling, or synthetic generation without permission from the rights holder.

An AIAPS-protected recording includes: a registered AIAPS record, a robust audio fingerprint, an embedded AIAPS watermark, and an optional metadata notice. Together these components provide a persistent identity and verification mechanism for protected recordings.

Document Info
StatusPublic Draft
Version1.0
Date2026
ScopeAudio
StandardAIAPS

Section 02 — Purpose

Purpose

The purpose of AIAPS is to provide a standardized method for:

01Signaling that a recording is not authorized for AI training

02Associating recordings with a timestamped registry record

03Enabling later verification of protected recordings

04Establishing a persistent identity for recordings across normal distribution formats

AIAPS is intended for finished music releases, masters, and other publishable recordings.

Section 03 — Standard Mark

AIAPS Standard Mark

The AIAPS Standard Mark signals that a recording has been protected under the AI Audio Protection Standard.

AIAPS-PROTECTED

Unauthorized AI training prohibited.

The standard mark may appear in:

01Distribution pages

02Album liner notes

03Website descriptions

04Promotional materials

05Metadata fields where available

Use of the AIAPS Standard Mark indicates that the recording has been processed through an AIAPS-compatible protection workflow and registered in an AIAPS-compatible registry.

Section 04 — Protection Notice

Protection Notice

An AIAPS-protected recording should be accompanied by the following notice wherever practical.

Standard Notice

AIAPS-PROTECTED

Unauthorized AI training prohibited.

Extended Notice

AIAPS-PROTECTED

This recording may not be used for AI training, dataset ingestion, voice cloning, style modeling, or synthetic generation without permission from the rights holder.

The protection notice may appear in:

01Website pages

02Metadata

03Release notes

04Credits

05Distribution descriptions

06Promotional materials

Recommended public reference: aiaps-standard.org

Section 05 — Scope

Scope

AIAPS is a signal and verification standard, not a licensing framework.

AIAPS v1.0 applies to

01Finished music recordings

02Exported stereo masters

03Mono or stereo audio files submitted for protection

04Registry-backed protection records

AIAPS v1.0 does not define

01Licensing terms beyond the AI training prohibition notice

02DRM or playback restriction systems

03Source-session project protection

04Stem-level protection requirements

05Legal ownership adjudication

Section 06 — Core Terms

Definitions

6.1 — AIAPS Record

A registry-backed record representing a protected recording.

6.2 — AIAPS ID

A human-readable identifier assigned by the registry. Format: AIAPS-YYYY-NNNNNN. Example: AIAPS-2026-000184.

6.3 — Audio Fingerprint

A robust identifier derived from the audio content itself and designed to support identification despite common format or processing changes.

6.4 — Embedded Watermark

A hidden machine-detectable signal embedded within the protected audio.

6.5 — Registry

The system of record that stores AIAPS protection entries and associated identifiers.

6.6 — Verification

The process of analyzing an audio file to determine whether it contains a valid AIAPS protection signal and/or corresponds to an AIAPS registry record.

Section 07 — Required Components

Required Components of an AIAPS-Protected Recording

An AIAPS-protected recording must include the following components.

7.1

Registry Record

A registered entry associated with the protected recording.

7.2

Audio Fingerprint

A fingerprint derived from the audio content.

The fingerprint enables identification of the recording even when distributed through common transformations such as:

01Lossy compression

02Normalization

03Minor equalization

04Format conversion

7.3

Embedded Watermark

A hidden watermark encoded within the protected recording. The watermark is designed to remain inaudible to listeners while remaining detectable by compliant verification tools.

AIAPS v1.0 compliant systems should also write a metadata notice when supported by the file format.

Section 08 — Identifiers

AIAPS Identifiers

Each AIAPS-protected recording is associated with three identifiers.

8.1

Spectral Fingerprint

The spectral fingerprint is derived from repeatable analysis of time-frequency features within the audio signal.

Purpose:

01Identify recordings under common transformations

02Support registry lookup

03Assist with verification when metadata is absent

A compliant implementation must produce a stable fingerprint for the same underlying recording under normal distribution changes.

8.2

Embedded AIAPS Watermark

The watermark is embedded into psychoacoustically suitable regions of the audio signal.

The watermark payload encodes:

01Protocol version

02Policy code

03AIAPS record identifier

04Registration time representation

05Integrity check field

The watermark must remain inaudible under normal listening conditions while remaining detectable by compliant verification tools.

8.3

Registry Record

The registry stores the protection record and associated identifiers including:

01AIAPS ID

02Fingerprint

03Rights-holder account reference

04Track title

05Artist name

06Registration timestamp

07Policy designation

08Verification status fields

Section 09 — Policy Code

Policy Code

AIAPS v1.0 Policy

NO_AI_TRAINING

This recording is designated as prohibited for unauthorized AI training, dataset ingestion, voice cloning, style modeling, or synthetic generation without permission from the rights holder.

Future AIAPS versions may define additional policy codes.

Section 10 — Registration

Registration Requirements

A compliant AIAPS protection workflow must register the recording in an AIAPS-compatible registry at the time of protection or upon the next successful synchronization.

At minimum, the registry record must contain:

01AIAPS ID

02Fingerprint

03Artist name or declared rights-holder name

04Track title

05Registration timestamp

06Policy code

07Account linkage or ownership reference

The registry is the source of truth for AIAPS record issuance.

Section 11 — Verification

Verification Requirements

A compliant AIAPS verification tool must be capable of performing the following steps.

Verification Process

01Analyze the submitted audio

02Compute or recover AIAPS fingerprinting and watermark evidence

03Attempt watermark detection

04Attempt registry matching

05Report the result to the user

A verification result should indicate

01Whether an AIAPS watermark was detected

02Whether the fingerprint matched a registry entry

03The associated AIAPS ID, if available

04The confidence or certainty level

05The registration timestamp, where available

06The associated owner or rights-holder label, where permitted

Section 12 — Metadata

Metadata Notice

Where the file format permits, compliant AIAPS tools should write a visible metadata notice.

AIAPS-PROTECTED

Unauthorized AI training prohibited.

Verify: aiaps-standard.org/verify/{AIAPS-ID}

Metadata is informative and supportive, but metadata alone does not constitute AIAPS protection without registry association and watermark or fingerprint evidence.

Section 13 — ID Format

AIAPS ID Format

Format

AIAPS-YYYY-NNNNNN

YYYY Registration year

NNNNNN Zero-padded sequence number

The registry is responsible for issuing valid identifiers and ensuring uniqueness.

Section 14 — Compliance

Compliance

A tool may claim AIAPS v1.0 compatibility only if it performs all of the following.

01Generates an AIAPS-compliant fingerprint

02Embeds an AIAPS-compliant watermark

03Registers the protected recording in an AIAPS-compatible registry

04Supports AIAPS verification workflow

05Preserves required protocol fields and policy information

A tool that only writes metadata notices, only fingerprints audio, or only registers files without watermarking is not fully AIAPS-compliant under v1.0.

Section 15 — Implementation

Implementation Flexibility

AIAPS v1.0 defines the required functional components of the standard but does not require a single implementation method.

Compliant implementations may vary in:

01Spectral feature extraction techniques

02Masking analysis approaches

03Detection thresholds

04Storage backends

05User interface design

However, implementations must preserve interoperability with AIAPS verification and registry semantics.

Section 16 — Security

Security and Anti-Abuse Considerations

AIAPS-compliant systems should protect:

01Account authentication

02Token storage

03Registry integrity

04ID issuance

05Verification endpoints

06Replay and spoofing resistance where practical

Private secrets, signing procedures, and anti-tamper mechanisms do not need to be publicly disclosed in the specification.

Section 17 — Versioning

Versioning

AIAPS v1.0 is the initial public specification.

Future versions may expand:

01Policy codes

02Watermark payload fields

03Multi-file or stem workflows

04Clip-level detection standards

05Interoperability rules

06Public verification APIs

07Certification programs

Implementations should preserve protocol version signaling to support future evolution.

Section 18 — Public Language

Recommended Public Protection Language

For creators, platforms, labels, and distributors.

Standard

AIAPS Protection Certificate

Verified

AIAPS Protected — NO_AI_TRAINING

Rights Holder ReferenceRH-0041-7E
AIAPS IDAIAPS-2026-000184
Fingerprint7f3a · 91c2 · d4e8 · 05b6 · 3f1a
Registered2026-03-14T09:41:00Z
WatermarkEmbedded — Machine-detectable
StatusActive

Usage Policy

This recording is registered under the AI Audio Protection Standard (AIAPS) and is designated as not authorized for AI training, dataset ingestion, voice cloning, style modeling, or synthetic generation without permission from the rights holder.

AIAPS Registry — Verified Record

Rev. 1.0

Extended

AIAPS-PROTECTED

This recording may not be used for AI training, dataset ingestion, voice cloning, style modeling, or synthetic generation without permission from the rights holder.