2023
Autores
Lopes, A; Barboza, JR; Bernardes, G;
Publicação
2023 Immersive and 3D Audio: from Architecture to Automotive, I3DA 2023
Abstract
Immersive audio technologies have broadened postproduction strategies for spatial audio, gaining popularity among mainstream audiences. However, there is a lack of defined procedures and critical thinking regarding audio mixing guidelines for surround sound in popular music. In this context, we conducted an empirical study to identify trends concerning instrument position, trajectories, and dynamics from surround mixings. Furthermore, we assess the degree to which they differ from their stereo renderings. Seven award-winning songs in the Grammy category for Best Immersive Album were analyzed, including surround 5.1 and stereo versions. The study found consistent instrument positions in the songs, with rhythmic instruments and bass in the center, lead vocals spread across front channels, and harmonic instruments in wider positions. Solo instruments occupied left, right, and center channels, with dynamics emphasizing lead vocals and solos. Trajectories were rarely used, indicating channel-based thinking. Limited adoption of immersive audio dimensions and reliance on stereo techniques were observed, with no notable differences between the surround and stereo versions. Identified song outliers are discussed and offer avenues for exploration, highlighting the importance of diverse musical expressions in informing immersive audio mixing. © 2023 IEEE.
2023
Autores
Cao, Z; Magalhães, E; Bernardes, G;
Publicação
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract
We study the impact of sound design – soundscape, sound effects, and auditory notifications, namely earcons – on the player’s experience of serious games. Three sound design versions for the game Venci’s Adventures have been developed: 1) no sound; 2) standard sound design, including soundscapes and sound effects; and 3) standard sound design with auditory notification (namely, earcons). Perceptual experiments were conducted to evaluate the most suitable attention retention earcons from a diverse collection of timbres, pitch, and melodic patterns, as well as the user experience of the different sound design versions assessed in pairs (1 vs. 2 and 2 vs. 3). Our results show that participants (n= 23 ) perceive better user experience in terms of game playing competence, immersion, flow, challenge and affect, and enhanced attention retention when adopting standard sound design with the earcons. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
2023
Autores
Carvalho, N; Diogo, D; Bernardes, G;
Publicação
THE 10TH INTERNATIONAL CONFERENCE ON DIGITAL LIBRARIES FOR MUSICOLOGY, DLFM 2023
Abstract
We propose a method for computing the similarity of symbolically-encoded Portuguese folk melodies. The main novelty of our method is the use of a preprocessing melodic reduction at multiple hierarchies to filter the surface of folk melodies according to 1) pitch stability, 2) interval salience, 3) beat strength, 4) durational accents, and 5) the linear combination of all former criteria. Based on the salience of each note event per criteria, we create three melodic reductions with three different levels of note retention. We assess the degree to which six folk music similarity measures at multiple reduction hierarchies comply with collected ground truth from experts in Portuguese folk music. The results show that SIAM combined with 75th quantile reduction using the combined or durational accents best models the similarity for a corpus of Portuguese folk melodies by capturing approximately 84-90% of the variance observed in ground truth annotations.
2023
Autores
Forero, J; Mendes, M; Bernardes, G;
Publicação
ACM International Conference Proceeding Series
Abstract
This study explores the development of intelligent affective virtual environments generated by bimodal emotion recognition techniques and multimodal feedback. A semantic and acoustic analysis predicts emotions conveyed by spoken language, fostering an expressive and transparent control structure. Textual contents and emotional predictions are mapped to virtual environments in real locations as audiovisual feedback. To demonstrate the application of this system, we developed a case study titled "En train d'oublier,"focusing on a train cemetery in Uyuni, Bolivia. The train cemetery holds historical significance as a site where abandoned trains symbolize the passage of time and the interaction between human activities and nature's reclamation. The space is transformed into an immersive and emotionally poetic experience through oral language and affective virtual environments that activate memories, as the system utilizes the transcribed text to synthesize images and modifies the musical output based on the predicted emotional states. The proposed bimodal emotion recognition techniques achieve 94% and 89% accuracy. The audiovisual mapping strategy allows for considering divergence in predictions generating an intended tension between the graphical and the musical representation. Using video and web art techniques, we experimented with the environments generated to create diverses poetic proposals. © 2023 ACM.
2018
Autores
Aly, L; Penha, R; Bernardes, G;
Publicação
Encyclopedia of Computer Graphics and Games
Abstract
2024
Autores
Aly, L; Godinho, L; Bota, P; Bernardes, G; da Silva, HP;
Publicação
SCIENTIFIC DATA
Abstract
Emotions encompass physiological systems that can be assessed through biosignals like electromyography and electrocardiography. Prior investigations in emotion recognition have primarily focused on general population samples, overlooking the specific context of theatre actors who possess exceptional abilities in conveying emotions to an audience, namely acting emotions. We conducted a study involving 11 professional actors to collect physiological data for acting emotions to investigate the correlation between biosignals and emotion expression. Our contribution is the DECEiVeR (DatasEt aCting Emotions Valence aRousal) dataset, a comprehensive collection of various physiological recordings meticulously curated to facilitate the recognition of a set of five emotions. Moreover, we conduct a preliminary analysis on modeling the recognition of acting emotions from raw, low- and mid-level temporal and spectral data and the reliability of physiological data across time. Our dataset aims to leverage a deeper understanding of the intricate interplay between biosignals and emotional expression. It provides valuable insights into acting emotion recognition and affective computing by exposing the degree to which biosignals capture emotions elicited from inner stimuli.
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