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About

About

Gilberto Bernardes holds a Ph.D. in Digital Media (2014) by the Universidade do Porto under the auspices of the University of Texas at Austin and a Master of Music 'cum Lauda' (2008) by Amsterdamse Hogeschool voor de Kunsten. Bernardes is currently an Assistant Professor at the Universidade do Porto and a Senior Researcher at the INESC TEC where he leads the Sound and Music Computing Lab. He counts with more than 90 publications, of which 14 are articles in peer-reviewed journals with a high impact factor (mostly Q1 and Q2 in Scimago) and fourteen chapters in books. Bernardes interacted with 152 international collaborators in co-authoring scientific papers. Bernardes has been continuously contributing to the training of junior scientists, as he is currently supervising six Ph.D. thesis and concluded 40+ Master dissertations.


He received nine awards, including the Fraunhofer Portugal Prize for the best Ph.D. thesis and several best paper awards at conferences (e.g., DCE and CMMR). He has participated in 12 R&D projects as a senior and junior researcher. In the past eight years, following his PhD defense, Bernardes was able to attract competitive funding to conduct a post-doctoral project funded by FCT and an exploratory grant for a market-based R&D prototype. Currently, he is leading the Portuguese team (Work Package leader) at INESC TEC on the Horizon Europe project EU-DIGIFOLK, and the Erasmus+ project Open Minds. His latest contribution focuses on cognitive-inspired tonal music representations and sound synthesis In his artistic activities, Bernardes has performed in some distinguished music venues such as Bimhuis, Concertgebouw, Casa da Música, Berklee College of Music, New York University, and Seoul Computer Music Festival.

Interest
Topics
Details

Details

  • Name

    Gilberto Bernardes Almeida
  • Role

    Senior Researcher
  • Since

    14th July 2014
005
Publications

2025

Evaluation of Lyrics Extraction from Folk Music Sheets Using Vision Language Models (VLMs)

Authors
Sales Mendes, A; Lozano Murciego, Á; Silva, LA; Jiménez Bravo, M; Navarro Cáceres, M; Bernardes, G;

Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract
Monodic folk music has traditionally been preserved in physical documents. It constitutes a vast archive that needs to be digitized to facilitate comprehensive analysis using AI techniques. A critical component of music score digitization is the transcription of lyrics, an extensively researched process in Optical Character Recognition (OCR) and document layout analysis. These fields typically require the development of specific models that operate in several stages: first, to detect the bounding boxes of specific texts, then to identify the language, and finally, to recognize the characters. Recent advances in vision language models (VLMs) have introduced multimodal capabilities, such as processing images and text, which are competitive with traditional OCR methods. This paper proposes an end-to-end system for extracting lyrics from images of handwritten musical scores. We aim to evaluate the performance of two state-of-the-art VLMs to determine whether they can eliminate the need to develop specialized text recognition and OCR models for this task. The results of the study, obtained from a dataset in a real-world application environment, are presented along with promising new research directions in the field. This progress contributes to preserving cultural heritage and opens up new possibilities for global analysis and research in folk music. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

2025

Exploring the Role of Sound Design in Serious Games: Impact on User Experience and Learning Outcomes

Authors
Zijing Cao; António Pinto; Gilberto Bernardes;

Publication
Proceedings of the 17th International Conference on Computer Supported Education

Abstract

2025

Sound Design for Electric Vehicles: Enhancing Safety and User Experience Through Acoustic Vehicle Alerting System (AVAS)

Authors
Rodrigues Ferraz Esteves, AR; Campos Magalhães, EM; Bernardes de Almeida, G;

Publication
SAE Technical Paper Series

Abstract
<div class="section abstract"><div class="htmlview paragraph">Silent motors are an excellent strategy to combat noise pollution. Still, they can pose risks for pedestrians who rely on auditory cues for safety and reduce driver awareness due to the absence of the familiar sounds of combustion engines. Sound design for silent motors not only tackles the above issues but goes beyond safety standards towards a user-centered approach by considering how users perceive and interpret sounds. This paper examines the evolving field of sound design for electric vehicles (EVs), focusing on Acoustic Vehicle Alerting Systems (AVAS). The study analyzes existing AVAS, classifying them into different groups according to their design characteristics, from technical concerns and approaches to aesthetic properties. Based on the proposed classification, an (adaptive) sound design methodology, and concept for AVAS are proposed based on state-of-the-art technologies and tools (APIs), like Wwise Automotive, and integration through a functional prototype within a virtual environment. We validate our solution by conducting user tests focusing on EV sound perception and preferences in rural and urban environments. Results showed participants preferred nature-like and melodic sounds with a wide range of frequencies, emphasizing 1000Hz, in rural areas, for the AVAS. For the interior experience, melodic, reliable, and relaxing sounds with a frequency range from 200Hz to 500Hz. In urban areas, melodic, futuristic, but not overpowering sounds (80Hz to 700Hz) with balanced frequencies at high speeds were chosen for the car's exterior. In the interior, melodic, futuristic, and combustion engine-like sounds with a low frequencies background and higher frequencies at high speeds were also preferred.</div></div>

2024

Dynamic Music Generation: Audio Analysis-Synthesis Methods

Authors
Bernardes, G; Cocharro, D;

Publication
Encyclopedia of Computer Graphics and Games

Abstract
[No abstract available]

2024

Biosensing in Interactive Art: A User-Centered Taxonomy

Authors
Aly, L; Penha, R; Bernardes, G;

Publication
Encyclopedia of Computer Graphics and Games

Abstract
[No abstract available]

Supervised
thesis

2023

VoxiGrain 1 - an Adaptive Music Instrument

Author
Sérgio Miguel Ferreira de Azevedo Coutinho

Institution
UP-FEUP

2023

INSTRUMENT POSITION IN IMMERSIVE AUDIO: A STUDY ON GOOD PRACTICES AND COMPARISON WITH STEREO APPROACHES

Author
Afonso Breda Lopes

Institution
UP-FEUP

2023

Emotion-driven Physiological Actor Dynamics For Interactive Theatre Sound

Author
Luís Alberto Teixeira Aly

Institution
UP-FEUP

2023

Towards Human-in-the-Loop Computational Rhythm Analysis in Challenging Musical Conditions

Author
António Humberto e Sá Pinto

Institution
UP-FEUP

2023

Towards a Cross-Disciplinary Sound Design Methodology: A Focus on Semiotics and Linguistics

Author
Bruno Miguel Guimarães Mascarenhas

Institution
UP-FEUP