AMS and genre classification using timbre, rhythm and tempo models

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Towards efficient music genre classification using FastMap

Automatic genre classification aims to correctly categorize an unknown recording with a music genre. Recent studies use the Kullback-Leibler (KL) divergence to estimate music similarity then perform classification using k-nearest neighbours (k-NN). However, this approach is not practical for large databases. We propose an efficient genre classifier that addresses the scalability problem. It uses a combination of modified FastMap algorithm and KL divergence to return the nearest neighbours then use 1- NN for classification. Our experiments showed that high accuracies are obtained while performing classification in less than 1/20 second per track

Enhancing timbre model using MFCC and its time derivatives for music similarity estimation

One of the popular methods for content-based music similarity estimation is to model timbre with MFCC as a single multivariate Gaussian with full covariance matrix, then use symmetric Kullback-Leibler divergence. From the field of speech recognition, we propose to use the same approach on the MFCCs’ time derivatives to enhance the timbre model. The Gaussian models for the delta and acceleration coefficients are used to create their respective distance matrix. The distance matrices are then combined linearly to form a full distance matrix for music similarity estimation. In our experiments on two datasets, our novel approach performs better than using MFCC alone.Moreover, performing genre classification using k-NN showed that the accuracies obtained are already close to the state-of-the-art

Benchmarking zero-shot and few-shot approaches for tokenization, tagging, and dependency parsing of Tagalog text

The grammatical analysis of texts in any human language typically involves a number of basic processing tasks, such as tokenization, morphological tagging, and dependency parsing. State-of-the-art systems can achieve high accuracy on these tasks for languages with large datasets, but yield poor results for languages such as Tagalog which have little to no annotated data. To address this issue for the Tagalog language, we investigate the use of auxiliary data sources for creating task-specific models in the absence of annotated Tagalog data. We also explore the use of word embeddings and data augmentation to improve performance when only a small amount of annotated Tagalog data is available. We show that these zero-shot and few-shot approaches yield substantial improvements on grammatical analysis of both in-domain and out-of-domain Tagalog text compared to state-of-the-art supervised baselines.Comment: To appear at PACLIC 2022. 10 pages, 2 figures, 4 table

Low-Complexity Physical Layer Security Scheme for Heterogeneous Cellular Networks based on Coordinated Precoding Design and Artificial Noise Generation

The undertaking for higher capacity and seamless wireless connectivity in next-generation mobile networks while maintaining an energy-efficient transmission requires a fundamental redesign of the existing cellular architecture. Heterogeneous network (HetNet) deployment is a promising architectural framework for meeting these design goals. However, an increase in cellular capacity and device connectivity would also result in an increase of sensitive data and classified information being exchanged over the network, thus making security another critical aspect in cellular network design. In this study, a convex optimization model was formulated that minimizes the total power consumption of the network while satisfying certain level of per-user data rate requirement and information secrecy at the physical layer. From this model, a low-complexity physical layer security scheme was developed that exploits coordinated precoding design, artificial noise generation, and a suboptimal sleep mode strategy in HetNets. Simulation results show that joint optimization of coordinated precoding scheme and artificial noise generation is an effective approach for increasing cellular capacity while simultaneously lowering the transmit power of the base stations and risk of eavesdropping attacks. Incorporating sleep mode mechanism in physical layer security transmission scheme of HetNets also reduced the total power consumption while maintaining a secured and reliable communication during low traffic periods. Furthermore, our proposed physical layer security scheme exhibited significant reduction in computational complexity, but at the expense of slight performance degradation in terms of energy efficiency

Detecting the quantum zero-point motion of vortices in the cuprate superconductors

We explore the experimental implications of a recent theory of the quantum dynamics of vortices in two-dimensional superfluids proximate to Mott insulators. The theory predicts modulations in the local density of states in the regions over which the vortices execute their quantum zero point motion. We use the spatial extent of such modulations in scanning tunnelling microscopy measurements on the vortex lattice of BSCCO to estimate the inertial mass of a point vortex. We discuss other, more direct, experimental signatures of the vortex dynamics.Comment: 24 pages, 5 figures; expanded version of cond-mat/0502002, with details of calculation

Scientific Opinion on Flavouring Group Evaluation 7, Revision 5 (FGE.07Rev5) : saturated and unsaturated aliphatic secondary alcohols, ketones and esters of secondary alcohols and saturated linear or branched‐chain carboxylic acids from chemical group 5

Acknowledgements: The Panel wishes to thank the members of the Working Group on Flavourings: Ulla Beckman Sundh, Leon Brimer, Karl-Heinz Engel, Paul Fowler, Rainer Gürtler, Trine Husøy, Wim Mennes and Gerard Mulder for the preparatory work on this scientific opinion and the Working Group on Genotoxicity: Mona-Lise Binderup, Claudia Bolognesi, Riccardo Crebelli, Rainer Gürtler, Francesca Marcon, Daniel Marzin and Pasquale Mosesso for the preparatory work on this scientific opinion and the hearing experts: Vibe Beltoft and Karin Nørby, and EFSA staff: Maria Anastassiadou, Maria Carfi and Annamaria Rossi for the support provided to this scientific opinion.Publisher PD

Scientific Opinion on Flavouring Group Evaluation 302 (FGE.302): N-(2-methylcyclohexyl)-2,3,4,5,6-pentafluoro-benzamide from Chemical Group 30

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Scientific Opinion on Flavouring Group Evaluation 63, Revision 3 (FGE.63Rev3): aliphatic secondary alcohols, ketones and related esters evaluated by JECFA (59th and 69th meetings) structurally related to saturated and unsaturated aliphatic secondary alcohols, ketones and esters of secondary alcohols and saturated linear or branched-chain carboxylic acids evaluated by EFSA in FGE.07Rev4

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