Introducing a new tool, UGSeeker, that identifies hard-to-find UGC, and the opportunities it creates for music rightsholders.
As the music industry continues to evolve with the help of technology, new solutions are emerging to tackle long-standing problems. One such solution is UGSeeker, a new tool developed by Song Sleuth, designed to unearth UGC that is easily missed online.
The Problem: Music Copyright Infringement
The music industry is currently facing a data crisis. Firstly, the current handling of user-generated content (UGC) is problematic on multiple levels. The data associated with UGC is often unorganised and outdated in its formatting, making it difficult to utilise effectively. Additionally, there is a lack of a single central authoritative source to determine ownership rights, resulting in conflicting information across multiple databases. This is further compounded by the issue of inadequate payout methods, as UGC is often compensated on a “market share” basis without taking into account the distinct characteristics of UGC versus original recordings and usage.
Secondly, there is a fundamental flaw in the current systems in place. YouTube, which relies on technologies such as Content ID and Melody ID, and current market solutions all use the same audio fingerprinting technology, which can only create an effective match to a master recording, rendering it ineffective in identifying any variations or covers that deviate from the original. This flaw in the system is a major obstacle in addressing the issue of unlicensed use of copyrighted music.
According to YouTube’s internal reports, the platform paid $6 billion to the music industry between June 2021 and June 2022, with $2 billion coming from UGC. As artists and labels increasingly rely on streaming revenue and UGC becomes more popular on short-format video platforms, music copyright claims represent a significant source of income for rightsholders.
Efforts to Solve the Problem
As mentioned previously, YouTube has implemented a system called Content ID, which automatically matches the audio in newly uploaded videos with saved audio in the platform’s database in order to facilitate copyright claims. However, the system is mainly effective for master recordings identification, and not all videos are picked up by Content ID.
Additionally, the Manual Claiming Tool can be a helpful complement to the previously mentioned system. However, it should be noted that manual claiming is not available to everyone. The Tool is only available to partners that need it and have “advanced working knowledge of copyright and Content ID”, as stated by Youtube.
The Content ID system is designed to automatically identify copyrighted music, but manual claiming requires rights owners to specify the specific time stamps of their music being used for video creators to understand which portions are being claimed. Therefore, manual claiming is more time-consuming and resource-intensive for rights owners.
If you’re interested in learning more about the distinctions between these two systems and how rightsholders can claim ownership of UGC on YouTube, read the article “How can rightsholders claim undiscovered royalties in user-generated content on YouTube?“.
The Solution: UGSeeker
UGSeeker is an AI platform developed by Song Sleuth to address the problem of tracking hard-to-find UGC. Like Content ID, it matches UGC online with corresponding tracks in a database. However, it differs from Content ID in its ability to detect ‘dirty audio’ UGC – that is, content whose audio has been distorted due to background noise, remixing, and live performance variations. After the AI technology identifies these videos, a human moderator reviews the content and insights, allowing clients to access ready-to-claim content.
Possibilities
The implementation of UGSeeker has ensured that music rightsholders can identify online assets that were previously extremely difficult to find. By identifying user-uploaded assets that traditional systems cannot find, Song Sleuth has provided insights that represent attractive marketing opportunities besides providing additional revenue opportunities. By identifying user-uploaded assets that traditional systems cannot detect, Song Sleuth has provided valuable insights that can aid in marketing efforts and create additional revenue opportunities.
