Jorge-Perianez-Pascual | INTIA

MetrikaBox: An open framework for experimenting with audio classification

Thu, 28 Aug 2025 00:00:00 +0000

We open the (Metrika)Box

Thu, 28 Aug 2025 00:00:00 +0000

After months in the making, instead of keeping the information locked away like in a mystery box, we’ve finally opened it! Our lab is proud to share with you the distilled essence of our work: “MetrikaBox: An open framework for experimenting with audio classification”. The title says it all—no further notes needed.

With this publication, Jorge Perianez-Pascual’s PhD journey reaches a turning point, as it brings together years of research in a single paper. As described there, MetrikaBox’s impact is significant: it has supported the development of many papers and experiments, and it lies at the core of MetrikaMedia, a UEx spin-off company that defines itself as a SaaS solution for multimedia content measurement. And now, it’s available for everyone to explore! What will you do with it? Read the paper, play with the code—and don’t forget to tell us about it!

MetrikaBox is one of the main outcomes of musicgenia, a project funded by Grant CPP2021-008491 from MICIU/AEI/10.13039/50100011033 and by the European Union through NextGenerationEU/PRTR. The goal of musicgenia is to develop a cloud-based platform that provides AI-generated production music as a service for content creators and media, both online (live music generation) and offline (pre-recorded music generation). The platform brings clear benefits: (1) royalty-free music, (2) fully original compositions, (3) an easy way to find music that fits your content, and (4) flexible streaming options, where you pay per second instead of per song.

Beyond Spectrograms: Rethinking Audio Classification from EnCodec's Latent Space

Sun, 16 Feb 2025 00:00:00 +0000

i3lab at the AI and SE Winter School in Doha, Qatar

Sun, 19 Jan 2025 00:00:00 +0000

From January 19 to 22, two members of i3lab, Pery and Emilio, participated in the Winter School on Artificial Intelligence and Software Engineering organized by the University of Doha for Science and Technology (UDST) in Doha, Qatar.

This event brought together experts, researchers and professionals from around the world to discuss the latest advances in artificial intelligence (AI) and software engineering (SE), two fundamental disciplines for the development of emerging technologies. During four days of conferences, workshops and hands-on sessions, participants explored key areas such as:

✅ Deep learning and generative models, with applications in computer vision, natural language processing and content generation.

✅ AI-driven software development, addressing new methodologies and tools to optimize the creation and maintenance of intelligent systems.

✅ Ethics and regulation in artificial intelligence, a crucial topic in the context of responsible implementation of AI models in society.

✅ AI integration in critical software systems, including applications in healthcare, security and industrial automation.

In addition to academic and technical training, the Winter School allowed i3lab to strengthen its international collaboration network, share experiences with other researchers and explore new ideas for applying Deep Learning in intelligent software development.

The stay in Doha also provided the opportunity to learn more about Qatar’s culture and innovation ecosystem, a country that is strongly betting on artificial intelligence and digital transformation.

We thank UDST for the excellent organization of the event and all speakers and attendees for the enriching discussions. Without a doubt, this experience will bring new perspectives and opportunities for research and development at i3lab.

💡 We keep advancing at the intersection of AI and software engineering! 🚀🔬

If you’d like to know more about our research lines in applying AI to software development, get in touch with us and we’ll tell you about it.

ADAPIMMA

Tue, 04 Jul 2023 11:31:59 +0200

Copyright management in Spain has always been a hot-button issue that has sparked great controversy. Special mention deserves the management of copyright for musical pieces. To manage these rights there is SGAE (General Society of Authors and Publishers) which maintains a certain monopoly. Copyright management is governed by the Intellectual Property Law, which in its 1996 version is somewhat vague regarding distribution criteria. So vague is the wording that it is not clear how SGAE charges broadcasting entities, such as radio stations. In some cases it is done based on the billing volume of the broadcasting entity, applying a percentage. That is, it is independent of the music used by the station and, being so, there is no way to make a fair distribution among the authors who provide that music. In other cases, estimates of music usage are made and based on that the management company bills. This can produce situations where young talented authors with short and less established careers are not receiving adequate compensation for their work and may be discouraged from continuing their career in this field.

Precisely the objective of this project is to investigate the techniques that would allow developing a system capable of i) discriminating the use made of music in radio media according to its classification in the new Intellectual Property Law (solution to the first problem) and ii) associating the exact use made of the musical piece to its original author in order to make an equitable distribution of copyright royalties (solution to the second problem). The development of this proposal would represent a significant innovation in the music world that could be an important source, not only of potential clients worldwide, but also of international investments that allow the internationalization of the Extremadura ICT model, both fundamental lines of the Employment, Entrepreneurship and Innovation axis of the Regional Green and Circular Economy Strategy, Extremadura 2030. Notably, due to its evolution and potential trajectory in Extremadura, the ICT sector is an active hub of transversal technology production and a driver of the establishment of software development companies, which can be considered green companies as they do not generate waste.

Results

The article “A Hybrid Multidimensional Recommender System for Radio Programs”, published in the journal “Expert Systems with Applications” by Elsevier, is a direct result of this project.

Its source code is available through two GitHub projects:

A demo is also available.

Metrikamedia at Foro Conecta Empresas 2022

Thu, 24 Nov 2022 09:30:00 +0000

On Thursday, November 24, 2022, as part of the technology showroom Foro Conecta Empresas, Metrikamedia, a spin-off of the UEx, presents one of the technologies developed by their company, which is used to separate voice and music within radio broadcasts in order to facilitate auditing by advertisers and control companies. As a demonstration of the platform’s usefulness, visitors who wish to do so can try to identify a piece of music playing in the background while a speaker talks.

Attendance at the event is free and no reservation is required. Don’t miss the opportunity to chat with those responsible for applying Artificial Intelligence techniques in real projects.

Music generation through deep learning

Mon, 03 Oct 2022 00:00:00 +0000

On November 3 and 4, as part of the Computer Science Doctoral Program at the University of Almería, Roberto Rodríguez Echeverría, University of Extremadura, delivered the course Content and/or recognizable pattern generation through neural networks, with the participation of Jorge Periánez Pascual, MetrikaMedia.

“It has been a while since relying on artificial intelligence to help us in our daily work stopped being a dream and became a reality. On a daily basis we use machine learning models to suggest the next words we type on our phones, to give just one example. What we never would have imagined is that these artificial intelligences would help us create creative content such as code for our programs, images following textual descriptions or, as we explain in this seminar, music,” commented UEx Associate Professor Roberto Rodríguez Echeverría.

The seminar content was as follows:

Introduction to deep learning
Recurrent Networks and Transformers
Content Generation
Image Generation with Variational Autoencoders
Music generation with LSTM and Transformers

This and other seminars are the result of collaboration between industry and University. From i3lab, one of the working groups of Quercus Software Engineering Group, we are committed to training new engineers in subjects such as artificial intelligence and everything related to it, such as MLOps. Interested? Get in touch with us and let’s talk.

A Hybrid Multidimensional Recommender System for Radio Programs

Sat, 20 Feb 2021 00:00:00 +0000

Testing challenges for NLP-intensive bots

Fri, 01 Jan 2021 00:00:00 +0000

Towards the optical character recognition of DSLs

Wed, 01 Jan 2020 00:00:00 +0000