A detailed examination of how Song Sleuth plays an important role in solving the music industry’s vast UGC problem through the identification of undiscovered royalties.
New technological developments have facilitated processes and further developments in various industries, and the music industry is no exception. Innovative companies are finding useful ways to integrate tech developments to the benefit of music labels and publishers, particularly to identify content that is not being monetised by their rightful owners.
But first, let’s recap a bit and start at the beginning. If you’re curious about understanding how Song Sleuth helps rights owners claim undiscovered royalties, look no further as we break it down.
What Is AI and Machine Learning?
Firstly, before we further explore this topic, it’s important to have coherent notions of what certain concepts are. When machine learning is mentioned, we are talking about a specific piece of technology that doesn’t need direct human instructions – it can learn and adapt by itself. According to TechTarget, this tech can make inferences from data patterns.
The potential of this technology is overwhelming. Many tasks currently performed by humans can be performed more efficiently by computers and this is what artificial intelligence is all about: the development of computer systems that can perform tasks that would in the past require human intelligence.
Application to the Music Industry
Back in the day, our access to music was restricted to the purchase of CDs, vinyl, or other physical formats. However, today we have access to all of the world’s discography and more through our smartphones. The streaming platforms democratised music access and social media has allowed for the free distribution, promotion, and usage of audio content.
This wide usage has made things more difficult for people or organisations in control of music rights. As we’ve briefly mentioned, these can be:
Music publishers: an organisation that puts together all the necessary elements, structure and composition of a song. Just like a recipe has its specific ingredient composition, each song also has the ingredients that make it a musical work.
Record Labels: these are responsible for recording the musical composition, and creating the final product – the songs we listen to every day – among many other things.
MCN and Distributors: organisations which are responsible for distributing music through its different channels for audience consumption.
PRO and CMO: organisations that enable the rightful rights owners to receive the royalties collected from different types of use.
Investment Funds: Artists and songwriters are ultimately the ones that should benefit the most from efficient royalty collection actions. Investment funds are further organisations owning music rights – relatively new key players emerging from the dynamics of the music industry.
Nowadays, music consumption is not only spread over a larger number of platforms but is also used in different formats. The audience has now the possibility to be more than a simple passive consumer, and instead an active creator of content by using songs and tunes available online, free of charge.
You have probably already encountered user-generated content before and it may be most of the content the algorithm picks for you across different platforms. User-generated content, or UGC, includes photos, videos, posts, comments and audio, uploaded by members of the public online. So whenever a creator or platform user uses a master recording to create further content, that new piece is considered UGC.
With so much data being created things can get messy. Firstly, data is formatted and moved around in an unstructured and antiquated way, through various authoritative sources, instead of a centralised one. Secondly, current market solutions all use similar audio fingerprinting technology which is mostly only able to create an effective match to a master recording. This renders them unfit for the purpose of identifying anything that is not the master recording.
Song Sleuth & UGSeeker
Even though AI might be a great tool to help identify unclaimed music rights, it is not an easy task to put it into practice.
This is where Song Sleuth can make a meaningful contribution. We solve the industry’s vast UGC problem by using our proprietary technology to find and verify content. We don’t rely on traditional audio fingerprinting, meaning we can ‘find the unfindable’ – content that all other platforms are unable to detect.
UGSeeker is our flagship product. An AI and machine learning platform that helps rights owners claim undiscovered royalties. It is able to find user-generated content of live music recordings and other unlicensed content that is being used, on Youtube.
After Song Sleuth’s AI algorithm spots these usage occasions and potential monetisation opportunities, they are reviewed by a human moderator to ensure 100% accuracy. Once the content is checked, it is then submitted for a monetization claim on behalf of the rights holder.
More Possibilities
Identifying undiscovered royalties represents a real opportunity, but the music industry is definitely not short of problems to solve.
Our database contains millions of user-uploaded assets from around the world which have never been available to analyse at scale. Having a strong insights tool that can inform stakeholders on new revenue, marketing and licensing opportunities is one of Song Sleuth’s goals, that’s why we built Live Link and Insights. But that’s for another article.
