Authenticity Verification

Authenticity and Provenance Verification

Starting with voice and music, Provenium helps rights teams verify what is authentic, synthetic, or misrepresented before monetization.

Request Demo Independent Verification Layer

Verification Report Snapshot

Status: Likely Authentic T + 00:38.2

The Solution

Segment-Based Audio Similarity Engine

01 Breaks every track into short vocal moments that can be reviewed independently

02 Builds a unique voice signature for each moment

03 Finds similar moments across recordings, including partial matches

04 Flags suspicious overlap with timestamped evidence

05 Generates a clear verification result for release and rights teams

Provenium delivers an evidence-backed verification system for rights-critical media decisions, not just another detection model.

The output is designed for business action: faster release decisions, lower legal exposure, and reusable trust records across partners.

How It Works

STEP 01

Track Intake

Your team uploads reference tracks and candidate tracks from your existing release workflow.

STEP 02

Voice Signature Creation

Each vocal segment is converted into a compact identity signature so voices can be compared consistently.

STEP 03

Music-Aware Matching

The system is tuned for real music conditions like production effects, register shifts, and expressive singing.

STEP 04

Evidence Collection

Instead of a black-box score, the platform collects where overlap happens and how strongly each segment supports the decision.

STEP 05

Decision and Action

Teams receive a verification outcome, confidence signals, and timestamps they can use for release approvals or dispute support.

Technology

How neural voice fingerprinting works

Provenium turns audio into measurable voice identity signatures. Tracks are split into short segments, and each segment is represented by a compact fingerprint that captures who is singing.

Why this approach wins in music

Music is harder than speech because voices shift with style, emotion, and production. Our system is built for singer verification, using a proven pretrained voice foundation adapted for music-specific similarity.

Segment-level analysis is resilient to noise, effects, and partial overlap, which makes it practical for real release pipelines.

How decisions are generated

Verification runs in two stages: fast candidate retrieval followed by detailed segment comparison. The platform shows what matched, when it matched, and how strongly the evidence supports the result.

Teams get decision-ready outputs with confidence signals and timestamps for release review, catalog checks, and dispute support.

Live Comparison Interface

Match Confidence

0.84 - Likely Authentic

Aligned Segments

00:12.1, 00:38.2, 01:07.9

Review Status

Evidence Bundle Ready