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  • My Sheet Music Transcriptions
  • Barcelona
  • 05:38 (UTC +02:00)
  • LinkedIn in/ocf

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@My-Sheet-Music-Transcriptions

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oriolcolomefont/README.md

Welcome to my GitHub.com profile! 👋

My name is Oriol Colomé i Font, and I am a Music Tech Generalist with over a decade of experience across the music industry and its wiggly-air-multimodal-cognitive-phenomenon we call MUSIC.

Currently, I'm leading innovation as Growth Lead & Product Owner at My Sheet Music Transcriptions, where I drive R&D and product development roadmaps, leveraging open-source technology and the right talent to position the company at the forefront of industry advancements.

What I do

I bridge the gap between artistic vision and technical implementation. My expertise spans:

  • Product Development & Strategy: Leading cross-functional teams and driving business growth through innovative music-tech solutions
  • Music Information Retrieval (MIR): Deep learning, audio signal processing, and computational music analysis
  • Technical Leadership: Python, PyTorch, Google Cloud Platform, and full-stack development collaboration
  • Music Industry Expertise: From performance and composition to music publishing and artist relations

My Journey

I've worked with full-stack developers and musicologists alike, built cross-functional teams, and driven business growth by bridging creative, technical, and strategic domains. My experience includes:

  • My Sheet Music Transcriptions (2022-Present): Growth Lead & Product Owner, Key Account Manager & Tech Lead
  • Epidemic Sound (2023): Master's Thesis Student in Music Information Research, researching deep music embeddings
  • Music Technology Group (MTG-UPF): Member of the Scientific Committee for the UPF-BMAT Chair in AI and Music
  • Freelance Musician (2014-Present): Performing, composing, arranging, and teaching across Europe

Education & Research

  • MSc in Sound and Music Computing - Universitat Pompeu Fabra (2021-2023)
  • MA in Music Theory and Composition - ESMUC (2019-2020)
  • BA in Music Performance - ESEM Taller de Músics (2014-2018)

My research focuses on high-level semantic abstractions closely aligned with cognitive processes related to music language and theory. The key question that drives my curiosity is: how can we flexibly and dynamically connect the high-resolution yet low-level representation of an electric signal through symbolic representations, systematic musicology, natural language, discrete representations, semantics, and cultural contexts—all within the framework of Western musical traditions?

Pinned Loading

  1. Uncovering-High-Level-Content-in-the-Time-Domain Uncovering-High-Level-Content-in-the-Time-Domain Public

    Leveraging self-supervised deep neural networks, inductive bias, and aural skills to learn deep audio embeddings with applications to boundary detection tasks.

    Jupyter Notebook 2

  2. arab-andal-motif-dev arab-andal-motif-dev Public

    Forked from satyajeetprabhu/arab-andal-motif-dev

    Towards a systematic exploration of motif development in Arab-Andalusian Music

    Jupyter Notebook

  3. Audio-Signal-Processing-For-Music-Applications Audio-Signal-Processing-For-Music-Applications Public

    Assignments for Audio Signal Processing for Music Applications on MTG-UPF Msc Sound And Music Computing. Note: It's for my personal learning purpose.

    Jupyter Notebook

  4. Melody-extraction-in-symphonic-music-recordings Melody-extraction-in-symphonic-music-recordings Public

    Algorithmic predominant melody extraction in in symphonic music recordings

    Jupyter Notebook

  5. The-Sound-of-AI-workshop The-Sound-of-AI-workshop Public

    The Sound of AI workshop on Generative Music

    Python 1