Songmine

Dig into your catalog

TM

Dig out long forgotten gems

for A&R and Synch by searching for songs with songs

Maximize Catalog 

Synch and Licensing Revenues
by onboarding Songmine

“I’ll know the right song when I hear it”.

But will you actually get around to hearing it?

 

Tens of thousands of songs are released every day to various music platforms, almost a million a month. Not to mention production music libraries and songs pitched to you directly. At the end of the day, you can only listen to a tiny fraction of what’s out there.

Songmine to the rescue!

MyPart's Songmine™ is the next-generation of song search and classification. It uses state-of-the-art “Song Mining” techniques to dig out songs that are worth your while, making sure you won’t miss them.

Transform Your Catalogue Into a Song Mine

 

Songmine™ boosts the efforts of all music or creative executives involved in daily searches for songs, whether for synch, A&R or any other purpose. It supports searching with a Benchmark, a set of five to fifteen songs that define your search or match your brief.

Once a Benchmark is selected, MyPart trains a machine learning model to deeply understand the reference songs provided,  It is then able to rank all the potential songs in the catalogue you are searching by likelihood of being relevant to that precise benchmark, to make sure that you hear the songs that are worth your while.  

Searching for song with songs

It’s hard to articulate precisely what you’re looking for with words, especially when looking for a song that elusively captures a feeling.

Well, what if you could also search for songs using the most natural query possible: other songs?

Lyrical and Compositional DNA

We created a game-changing song fingerprinting technique that abstracts the DNA of a song in a way that enables searching for songs with common harmonic, melodic, lyrical and structural features to your reference songs.


Care to learn more?

MyPart is a game changing AI platform 'leapfrogging' song search, allowing instant discovery of songwriting talent from around the globe and maximizing revenue for Music Publishers by pinpointing long forgotten gems in their massive catalogs. 

Our proprietary algorithms conduct deep and granular analysis of lyrical and musical relevance using advanced NLP and DSP feature extraction methods and state-of-the-art machine learning techniques, predicting the likelihood of relevance of any song to benchmarks of reference music defined by music executives.

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