Music Recognition Engine
Our Music Recognition Engine applies advanced Music Information Retrieval (MIR), neural audio embeddings and rights-aware metadata matching to detect, interpret and attribute music across any environment. Designed for CMOs, broadcasters and digital platforms, it delivers work-level identification, version recognition and copyright-relevant similarity analysis at scale.
Identifies music across live, broadcast and ambient audio using noise-robust MIR features and neural audio embeddings.
Detects cover reinterpretations, remixes and various related derivative works through work-level similarity modeling.
Maps recognized audio to ISWC, ISRC, composers, publishers and catalog data for rights-accurate usage reporting.
Identifies music across live, broadcast and ambient audio using noise-robust MIR features and neural audio embeddings.
Detects cover reinterpretations, remixes and various related derivative works through work-level similarity modeling.
Maps recognized audio to ISWC, ISRC, composers, publishers and catalog data for rights-accurate usage reporting.
The engine transforms raw audio into work-level usage data through a multi-stage MIR and metadata pipeline, ensuring accuracy, transparency and rights alignment across all environments.
The image illustrates how music recognition works using a visual analogy. Market-standard systems rely on exact matches – similar to recognizing Elvis Presley only when the image looks very close to the original. As soon as a song is covered, reinterpreted, performed live, or heavily transformed, these systems often fail to recognize it.
Nowon works differently. Just as we still recognize Elvis across very different visual styles, our work-level identification recognizes the same musical work across covers, reinterpretations, live performances, and AI-generated versions.
Slide to compare market-standard recognition with nowon’s approach.
The image below illustrates how music recognition works using a visual analogy. Market-standard systems rely on exact matches – similar to recognizing Elvis Presley only when the image looks very close to the original. As soon as a song is covered, reinterpreted, performed live, or heavily transformed, these systems often fail to recognize it.
Nowon works differently. Just as we still recognize Elvis across very different visual styles, our work-level identification recognizes the same musical work across covers, reinterpretations, live performances, and AI-generated versions.
Slide to compare market-standard recognition with nowon’s approach.
Designed for seamless use in large-scale live event monitoring, enabling people to capture, verify and manage performances across multiple venues with ease.
Use APIs and SDKs to integrate our music recognition, AI-traceability, broadcast analysis and metadata services into your existing systems.
