Onset Event Decoding Exploiting the Rhythmic Structure of Polyphonic Music

(c)2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Published version: IEEE Journal of Selected Topics in Signal Processing 5(6): 1228-1239, Oct 2011. DOI:10.1109/JSTSP.2011.214622

Symbolic music generation conditioned on continuous-valued emotions

In this paper we present a new approach for the generation of multi-instrument symbolic music driven by musical emotion. The principal novelty of our approach centres on conditioning a state-of-the-art transformer based on continuous-valued valence and arousal labels. In addition, we provide a new large-scale dataset of symbolic music paired with emotion labels in terms of valence and arousal. We evaluate our approach in a quantitative manner in two ways, first by measuring its note prediction accuracy, and second via a regression task in the valence-arousal plane. Our results demonstrate that our proposed approaches outperform conditioning using control tokens which is representative of the current state of the art.‘la Caixa’’ Foundation under Grant 100010434 and Grant LCF/BQ/DI19/1173003 - FCT—Foundation for Science and Technology, I.P., through the Project MERGE through the National Funds (PIDDAC) through the Portuguese State Budget under Grant PTDC/CCI-COM/3171/2021 - European Social Fund through the Regional Operational Program Centro 2020 Project CISUC under Grant UID/CEC/00326/2020info:eu-repo/semantics/publishedVersio

Reliability-Informed Beat Tracking of Musical Signals

Abstract—A new probabilistic framework for beat tracking of musical audio is presented. The method estimates the time between consecutive beat events and exploits both beat and non-beat information by explicitly modeling non-beat states. In addition to the beat times, a measure of the expected accuracy of the estimated beats is provided. The quality of the observations used for beat tracking is measured and the reliability of the beats is automatically calculated. A k-nearest neighbor regression algorithm is proposed to predict the accuracy of the beat estimates. The performance of the beat tracking system is statistically evaluated using a database of 222 musical signals of various genres. We show that modeling non-beat states leads to a significant increase in performance. In addition, a large experiment where the parameters of the model are automatically learned has been completed. Results show that simple approximations for the parameters of the model can be used. Furthermore, the performance of the system is compared with existing algorithms. Finally, a new perspective for beat tracking evaluation is presented. We show how reliability information can be successfully used to increase the mean performance of the proposed algorithm and discuss how far automatic beat tracking is from human tapping. Index Terms—Beat-tracking, beat quality, beat-tracking reliability, k-nearest neighbor (k-NN) regression, music signal processing. I

Beyond Music Information Retrieval: A Proposed Model for Automatic Generation of Dialogic Music

In this article we propose a generative music model that recombines heterogeneous corpora of audio units on both horizontal and vertical dimensions of musical structure. In detail, we describe a system that relies on algorithmic strategies from the feld of music information retrieval—in particular content-based audio processing strategies—to infer information from music recordings that, in turn, supervise generative music strategies. The model allows automatic remix and mashup creation and the manipulation of audio signals according to inferred stylistic features. In addition to widening the creative potential of non-experts, the model also expands knowledge in areas such as computational music analysis, generative music and music information retrieval

Improved timber harvest techniques maintain biodiversity in tropical forests

Tropical forests are selectively logged at 20 times the rate at which they are cleared, and at least a fifth have already been disturbed in this way. In a recent pan-tropical assessment, Burivalova et al. demonstrate the importance of logging intensity as a driver of biodiversity decline in timber estates. Their analyses reveal that species richness of some taxa could decline by 50% at harvest intensities of 38 m3 ha-1. However, they did not consider the extraction techniques that lead to these intensities. Here, we conduct a complementary meta-analysis of assemblage responses to differing logging practices: conventional logging and reduced-impact logging. We show that biodiversity impacts are markedly less severe in forests that utilise reduced-impact logging, compared to those using conventional methods. While supporting the initial findings of Burivalova et al., we go on to demonstrate that best practice forestry techniques curtail the effects of timber extraction regardless of intensity. Therefore, harvest intensities are not always indicative of actual disturbance levels resulting from logging. Accordingly, forest managers and conservationists should advocate practices that offer reduced collateral damage through best practice extraction methods, such as those used in reduced-impact logging. Large-scale implementation of this approach would lead to improved conservation values in the 4 million km2 of tropical forests that are earmarked for timber extraction

The Phantom Bounce: A New Oscillating Cosmology

An oscillating universe cycles through a series of expansions and contractions. We propose a model in which ``phantom'' energy with $p < -\rho$ grows rapidly and dominates the late-time expanding phase. The universe's energy density is so large that the effects of quantum gravity are important at both the beginning and the end of each expansion (or contraction). The bounce can be caused by high energy modifications to the Friedmann equation, which make the cosmology nonsingular. The classic black hole overproduction of oscillating universes is resolved due to their destruction by the phantom energy.Comment: Four pages, one figure. V3: version to appear in JCA

Local Periodicity-Based Beat Tracking for Expressive Classical Piano Music

To model the periodicity of beats, state-of-the-art beat tracking systems use "post-processing trackers" (PPTs) that rely on several empirically determined global assumptions for tempo transition, which work well for music with a steady tempo. For expressive classical music, however, these assumptions can be too rigid. With two large datasets of Western classical piano music, namely the Aligned Scores and Performances (ASAP) dataset and a dataset of Chopin's Mazurkas (Maz-5), we report on experiments showing the failure of existing PPTs to cope with local tempo changes, thus calling for new methods. In this paper, we propose a new local periodicity-based PPT, called predominant local pulse-based dynamic programming (PLPDP) tracking, that allows for more flexible tempo transitions. Specifically, the new PPT incorporates a method called "predominant local pulses" (PLP) in combination with a dynamic programming (DP) component to jointly consider the locally detected periodicity and beat activation strength at each time instant. Accordingly, PLPDP accounts for the local periodicity, rather than relying on a global tempo assumption. Compared to existing PPTs, PLPDP particularly enhances the recall values at the cost of a lower precision, resulting in an overall improvement of F1-score for beat tracking in ASAP (from 0.473 to 0.493) and Maz-5 (from 0.595 to 0.838).Comment: Accepted to IEEE/ACM Transactions on Audio, Speech, and Language Processing (July 2023

Latent ice recrystallization inhibition activity in nonantifreeze proteins : Ca2+-activated plant lectins and cation-activated antimicrobial peptides

Organisms living in polar regions have evolved a series of antifreeze (glyco) proteins (AFGPs) to enable them to survive by modulating the structure of ice. These proteins have huge potential for use in cellular cryopreservation, ice-resistant surfaces, frozen food, and cryosurgery, but they are limited by their relatively low availability and questions regarding their mode of action. This has triggered the search for biomimetic materials capable of reproducing this function. The identification of new structures and sequences capable of inhibiting ice growth is crucial to aid our understanding of these proteins. Here, we show that plant c-type lectins, which have similar biological function to human c-type lectins (glycan recognition) but no sequence homology to AFPs, display calcium-dependent ice recrystallization inhibition (IRI) activity. This IRI activity can be switched on/off by changing the Ca2+ concentration. To show that more (nonantifreeze) proteins may exist with the potential to display IRI, a second motif was considered, amphipathicity. All known AFPs have defined hydrophobic/hydrophilic domains, rationalizing this choice. The cheap, and widely used, antimicrobial Nisin was found to have cation-dependent IRI activity, controlled by either acid or addition of histidine-binding ions such as zinc or nickel, which promote its amphipathic structure. These results demonstrate a new approach in the identification of antifreeze protein mimetic macromolecules and may help in the development of synthetic mimics of AFPs