• Meta Research Conference, MERE 2022

  Hernández Leo, Davinia; Sánchez Reina, Jesús Roberto (Universitat Pompeu Fabra, 2023-06-09)

  The MERE Conference has become an annual tradition, showcasing the remarkable research work of students from the Master’s Programs in Sound and Music Computing, Intelligent and Interactive Systems, and Computational ...
• Empirically investigating virtual learning companions to enhance social media literacy

  Theophilou, Emily; Schwarze, Veronica; Börsting, Johanna; Sánchez Reina, Jesús Roberto; Scifo, Lidia; Lomonaco, Francesco; Aprin, Farbod; Ognibene, Dimitri; Taibi, Davide; Hernández Leo, Davinia; Eimler, Sabrina (Springer, 2023)

  Social media platforms provide opportunities for users across the world to connect and communicate between them and engage into acts of social support and entertainment. Yet it can also bring negative consequences as it ...
• State representation learning for goal-conditioned reinforcement learning

  Steccanella, Lorenzo; Jonsson, Anders (Springer, 2022)

  This paper presents a novel state representation for reward-free Markov decision processes. The idea is to learn, in a self-supervised manner, an embedding space where distances between pairs of embedded states correspond ...
• Efficient remote photoplethysmography with temporal derivative modules and time-shift invariant loss

  Comas, Joaquim; Ruiz Ovejero, Adrià; Sukno, Federico Mateo (Institute of Electrical and Electronics Engineers (IEEE), 2022)

  We present a lightweight neural model for remote heart rate estimation focused on the efficient spatio-temporal learning of facial photoplethysmography (PPG) based on i) modelling of PPG dynamics by combinations of multiple ...
• Networks of injectable microdevices powered and digitally linked by volume conduction for neuroprosthetics: a proof-of-concept

  Becerra Fajardo, Laura; Minguillon, Jesus; Comerma-Montells, Albert; Ivorra Cano, Antoni, 1974- (Institute of Electrical and Electronics Engineers (IEEE), 2023)

  Wireless power transfer (WPT) methods such as inductive coupling and ultrasounds are used as an alternative to electrochemical batteries to energize active implantable medical devices. However, existing WPT methods require ...
• Effectiveness of a mixed reality system in terms of social interaction behaviors in children with and without autism spectrum condition

  Galí Pérez, Olga; Sayis, Batuhan; Parés, Narcís, 1966- (ACM Association for Computer Machinery, 2021)

  The present study analyses the effectiveness of a mixed reality (MR) face-to-face full-body system to foster social interaction behaviors (SIBs) in a child with ASC and a play partner, a child without ASC (non-ASC). An MR ...
• FastLAS: scalable inductive logic programming incorporating domain-specific optimisation criteria

  Law, Mark; Russo, Alessandra; Bertino, Elisa; Broda, Krysia; Lobo, Jorge (Association for the Advancement of Artificial Intelligence (AAAI), 2020)

  Inductive Logic Programming (ILP) systems aim to find a set of logical rules, called a hypothesis, that explain a set of examples. In cases where many such hypotheses exist, ILP systems often bias towards shorter solutions, ...
• Exemplar-based image inpainting using an affine invariant similarity measure

  Fedorov, Vadim; Arias Martínez, Pablo; Facciolo Furlan, Gabriele; Ballester, Coloma (Springer, 2016)

  Patch-based approaches are used in state-of-the-art methods for image inpainting. This paper presents a new method for exemplar-based image inpainting using transformed patches. The transformation is determined for each ...
• ECTS: enhanced centralized TSCH scheduling with packet aggregation for industrial IoT

  Michaelides, Michael; Adame, Toni; Bellalta, Boris (Institute of Electrical and Electronics Engineers (IEEE), 2022)

  The Industrial Internet of Things (IoT) has gained a lot of momentum thanks to the introduction of Time Slotted Channel Hopping (TSCH) in IEEE 802.15.4. At last, we can enjoy collision-free, low-latency wireless communication ...
• A virtual reality system for the simulation of neurodiversity

  López-Carral, Héctor; Blancas Muñoz, Maria; Mura, Anna; Omedas, Pedro; España-Cumellas, Àdria; Martínez Bueno, Enrique; Milliken, Neil; Moore, Paul; Haque, Leena; Gilroy, Sean; Verschure, Paul F. M. J. (Springer, 2021)

  Autism is a neurodevelopmental disorder characterized by deficits in social communication and repetitive patterns of behavior. Individuals affected by Autism Spectrum Disorder (ASD) may face overwhelming sensory ...
• BAF: an audio fingerprinting dataset for broadcast monitoring

  Cortès, Guillem; Ciurana, Alex; Molina, Emilio; Miron, Marius; Meyers, Owen; Six, Joren; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2022)

  Audio Fingerprinting (AFP) is a well-studied problem in music information retrieval for various use-cases e.g. content-based copy detection, DJ-set monitoring, and music excerpt identification. However, AFP for continuous ...
• Music representation learning based on editorial metadata from Discogs

  Alonso-Jiménez, Pablo; Serra, Xavier; Bogdanov, Dmitry (International Society for Music Information Retrieval (ISMIR), 2022)

  This paper revisits the idea of music representation learning supervised by editorial metadata, contributing to the state of the art in two ways. First, we exploit the public editorial metadata available on Discogs, an ...
• A diffusion-inspired training strategy for singing voice extraction in the waveform domain

  Plaja-Roglans, Genís; Miron, Marius; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2022)

  Notable progress in music source separation has been achieved using multi-branch networks that operate on both temporal and spectral domains. However, such networks tend to be complex and heavy-weighted. In this work, we ...
• MusAV: a dataset of relative arousal-valence annotations for validation of audio models

  Bogdanov, Dmitry; Lizarraga Seijas, Xavier; Alonso-Jiménez, Pablo; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2022)

  We present MusAV, a new public benchmark dataset for comparative validation of arousal and valence (AV) regression models for audio-based music emotion recognition. To gather the ground truth, we rely on relative judgments ...
• Violin etudes: a comprehensive dataset for f0 estimation and performance analysis

  Can Tamer, Nazif; Ramoneda, Pedro; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2022)

  Violin performance analysis requires accurate and robust f0 estimates to give feedback on the playing accuracy. Despite the recent advancements in data-driven f0 estimators, their application to performance analysis remains ...
• In search of Sañcāras: tradition-informed repeated melodic pattern recognition in carnatic music

  Nuttall, Thomas; Plaja-Roglans, Genís; Pearson, Lara; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2022)

  Carnatic Music is a South Indian art and devotional musical practice in which melodic patterns (motifs and phrases), known as sañcaras Å , play a crucial structural and expressive role. We demonstrate how the combination ...
• Bottlenecks and solutions for audio to score alignment research

  Morsi, Alia; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2022)

  Although audio to score alignment is a classic Music Information Retrieval problem, it has not been defined uniquely with the scope of musical scenarios representing its core. The absence of a unified vision makes it ...
• Embed2Sym: scalable neuro-symbolic reasoning via clustered embeddings

  Aspis, Yaniv; Broda, Krysia; Lobo, Jorge; Russo, Alessandra (International Joint Conferences on Artificial Intelligence Organization, 2022)

  Neuro-symbolic reasoning approaches proposed in recent years combine a neural perception component with a symbolic reasoning component to solve a downstream task. By doing so, these approaches can provide neural networks ...
• Online symbolic learning of policies for explainable security

  Drozdov, Arthur; Law, Mark; Lobo, Jorge; Russo, Alessandra; Wilathgamuwage Don, Mercion (Institute of Electrical and Electronics Engineers (IEEE), 2021)

  Statistical Machine Learning (ML) has been proved to be an invaluable tool in many areas including privacy and security. On the other hand, recent advances in the field of Symbolic Learning have included novel scalable ...
• A security-constrained reinforcement learning framework for software defined networks

  Mudgerikar, Anand; Bertino, Elisa; Lobo, Jorge; Verma, Dinesh (Institute of Electrical and Electronics Engineers (IEEE), 2021)

  Reinforcement Learning (RL) is an effective technique for building ‘smart’ SDN controllers because of its model-free nature and ability to learn policies online without requiring extensive training data. However, as RL ...

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