2021
Authors
Aly, L; Silva, H; Bernardes, G; Penha, R;
Publication
Human Technology
Abstract
2021
Authors
Carvalho N.; Gonzalez-Gutierrez S.; Merchan Sanchez-Jara J.; Bernardes G.; Navarro-Cáceres M.;
Publication
ACM International Conference Proceeding Series
Abstract
Folk music is a fundamental immaterial heritage that promotes cultural identity. However, it lacks a substantial body of open access materials, and its promotion has been disconnected from the education curriculum. In this context, facilitated access to annotated high-quality folk music content can promote better educational tools and enhance cultural heritage literacy. Based on this, we advance and detail three main contributions: 1) a standardized model to musically annotate Iberian folk music; 2) a new database, named I-Folk, with annotated files following the proposed model; and 3) tools for navigating and retrieving folk music contents from the database. A particular emphasis is given to the educational application of the proposed model, contents, and tools in education. Ultimately, we strive for the promotion of Iberian folk music to the educators' community.
2021
Authors
Animashaun, A; Bernardes, G;
Publication
4th Symposium on Occupational Safety and Health Proceedings Book
Abstract
2021
Authors
Bernardo, G; Bernardes, G;
Publication
ACM International Conference Proceeding Series
Abstract
In this paper, we advance a multimodal optimization music mashup creation model for loop recombination at scale. The motivation to pursue such a model is to 1) tackle current scalability limitations in state-of-the-art (brute force) models while enforcing the 2) compatibility, i.e., recombination quality, of audio loops, and 3) a pool of diverse solutions that can accommodate personal user preferences or promote different musical styles. To this end, we adopt the Artificial Immune System (AIS) opt-aiNet algorithm to efficiently compute a population of compatible and diverse mashups from loop recombinations. Optimal mashups result from local minima in a feature space that objectively represents harmonic and rhythmic compatibility. We implemented our model as a prototype application named Mixmash-AIS, and conducted an objective evaluation that tackles three dimensions: loop recombination compatibility, mashups diversity, and computational model efficiency. The conducted evaluation compares the proposed system to a standard genetic algorithm (GA) and a brute force (BF) approach. While the GA stands as the most efficient algorithm, its poor results in terms of compatibility reinforce the primacy of the AIS opt-aiNet in efficiently finding optimal compatible loop mashups. Furthermore, the AIS opt-aiNet showed to promote a diverse mashup population, outperforming both GA or BF approaches. © 2021 Owner/Author.
2021
Authors
Cocharro, D; Bernardes, G; Bernardo, G; Lemos, C;
Publication
Perspectives on Music, Sound and Musicology
Abstract
2021
Authors
Lemos, C; Cocharro, D; Bernardes, G;
Publication
ACM International Conference Proceeding Series
Abstract
Rhythmic similarity, a fundamental task within Music Information Retrieval, has recently been applied in creative music contexts to retrieve musical audio or guide audio-content transformations. However, there is still very little knowledge of the typical rhythmic similarity values between overlapping musical structures per instrument, genre, and time scales, which we denote as rhythmic compatibility. This research provides the first steps towards the understanding of rhythmic compatibility from the systematic analysis of MedleyDB, a large multi-track musical database composed and performed by artists. We apply computational methods to compare database stems using representative rhythmic similarity metrics - Rhythmic Histogram (RH) and Beat Spectrum (BS) - per genre and instrumental families and to understand whether RH and BS are prone to discriminate genres at different time scales. Our results suggest that 1) rhythmic compatibility values lie between [.002,.354] (RH) and [.1,.881] (BS), 2) RH outperforms BS in discriminating genres, and 3) different time scale in RH and BS impose significant differences in rhythmic compatibility. © 2021 ACM.
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