MyPart Inc.
Doron Gabbay is an experienced communications and business leader in the music technology sector, currently serving as the Head of Communications and Business Lead for EMEA at MyPart Inc. since January 2021. Previously, Doron was the Executive Producer of Tune In Tel Aviv from June 2016 to December 2021, overseeing Israel's International Music Conference and Showcase Festival, and held the role of Managing Director at Oleh! Records, where efforts focused on promoting Israeli artists in the global music industry from December 2016 to November 2021. Additionally, Doron contributed to content policy at Taboola from February 2017 to August 2019. Doron Gabbay holds a Bachelor of Laws (LLB) from Tel Aviv University and Monash Law, with studies conducted from 2015 to 2019 and 2018, respectively.
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MyPart Inc.
MyPart is an AI-powered song search and matching platform for anyone in pursuit of songs, including the music industry, TV/Film and advertising.For Music and Creative Executives:MyPart’s award-winning technology uses reference songs- rather than conventional “tagging” techniques- to help A&Rs, Sync, and Music Supervisors “dig” throughand prioritize their musical catalogs and/or discover new talent. This helps these industry decision-makers find songs that share common harmonic, melodic, lyrical, sonic and structural features with their predefined benchmarks, and ensures they only listen to the “right” songs that actually match their needs. For Songwriters:MyPart’s AI analyzes songs submitted by emerging songwriters from all over the world, in order to place them with opportunities in the Music, TV/Film and Advertising Industries. We believe your songs deserve a shot, and create matches purely based on song relevance, rather than personal connections or industry access.MyPart graduated from Universal Music's exclusive Abbey Road RED program in London and Capitol Records' gBeta program in LA, as well as Deloitte's LaunchPad Growth program, and won the MassChallenge 2018 gold award and Music Week 2021 Tech Summit.Its proprietary 'Song Mining' engine conducts comprehensive and granular analysis of lyrical, musical and sonic relevance based on a wide technology stack that combines machine learning, computational linguistics, and digital signal processing to determine the likely relevance of any song to any set of reference songs. Our unique approach combines two key qualities:The ability to search for songs with a set of reference songs We created a song fingerprinting technique that abstracts song DNA to enable searching for songs with reference songs, based on common harmonic, melodic, lyrical, sonic and structural featuresA distinct focus on the semantics and aesthetics of song lyrics. At the heart of our distinct approach is a special focus on the deep comprehension of song lyrics