SPEAKER VGG CCT: Cross-corpus Speech Emotion Recognition with Speaker Embedding and Vision Transformers

In recent years, Speech Emotion Recognition (SER) has been investigated mainly transforming the speech signal into spectrograms that are then classified using Convolutional Neural Networks pretrained on generic images and fine tuned with spectrograms. In this paper, we start from the general idea above and develop a new learning solution for SER, which is based on Compact Convolutional Transformers (CCTs) combined with a speaker embedding. With CCTs, the learning power of Vision Transformers (ViT) is combined with a diminished need for large volume of data as made possible by the convolution. This is important in SER, where large corpora of data are usually not available. The speaker embedding allows the network to extract an identity representation of the speaker, which is then integrated by means of a self-attention mechanism with the features that the CCT extracts from the spectrogram. Overall, the solution is capable of operating in real-time showing promising results in a cross-corpus scenario, where training and test datasets are kept separate. Experiments have been performed on several benchmarks in a cross-corpus setting as rarely used in the literature, with results that are comparable or superior to those obtained with state-of-the-art network architectures. Our code is available at https://github.com/JabuMlDev/Speaker-VGG-CCT

Scaling of the Critical Function for the Standard Map: Some Numerical Results

The behavior of the critical function for the breakdown of the homotopically non-trivial invariant (KAM) curves for the standard map, as the rotation number tends to a rational number, is investigated using a version of Greene's residue criterion. The results are compared to the analogous ones for the radius of convergence of the Lindstedt series, in which case rigorous theorems have been proved. The conjectured interpolation of the critical function in terms of the Bryuno function is discussed.Comment: 26 pages, 3 figures, 13 table

Scaling law in the Standard Map critical function. Interpolating hamiltonian and frequency map analysis

We study the behaviour of the Standard map critical function in a neighbourhood of a fixed resonance, that is the scaling law at the fixed resonance. We prove that for the fundamental resonance the scaling law is linear. We show numerical evidence that for the other resonances $p/q$, $q \geq 2$, $p \neq 0$ and $p$ and $q$ relatively prime, the scaling law follows a power--law with exponent $1/q$.Comment: AMS-LaTeX2e, 29 pages with 8 figures, submitted to Nonlinearit

A Sparse and Locally Coherent Morphable Face Model for Dense Semantic Correspondence Across Heterogeneous 3D Faces

The 3D Morphable Model (3DMM) is a powerful statistical tool for representing 3D face shapes. To build a 3DMM, a training set of face scans in full point-to-point correspondence is required, and its modeling capabilities directly depend on the variability contained in the training data. Thus, to increase the descriptive power of the 3DMM, establishing a dense correspondence across heterogeneous scans with sufficient diversity in terms of identities, ethnicities, or expressions becomes essential. In this manuscript, we present a fully automatic approach that leverages a 3DMM to transfer its dense semantic annotation across raw 3D faces, establishing a dense correspondence between them. We propose a novel formulation to learn a set of sparse deformation components with local support on the face that, together with an original non-rigid deformation algorithm, allow the 3DMM to precisely fit unseen faces and transfer its semantic annotation. We extensively experimented our approach, showing it can effectively generalize to highly diverse samples and accurately establish a dense correspondence even in presence of complex facial expressions. The accuracy of the dense registration is demonstrated by building a heterogeneous, large-scale 3DMM from more than 9,000 fully registered scans obtained by joining three large datasets together

Enumeration of self avoiding trails on a square lattice using a transfer matrix technique

We describe a new algebraic technique, utilising transfer matrices, for enumerating self-avoiding lattice trails on the square lattice. We have enumerated trails to 31 steps, and find increased evidence that trails are in the self-avoiding walk universality class. Assuming that trails behave like $A \lambda ^n n^{11 \over 32}$, we find $\lambda = 2.72062 \pm 0.000006$ and $A = 1.272 \pm 0.002$.Comment: To be published in J. Phys. A:Math Gen. Pages: 16 Format: RevTe

Development of old-growth characteristics in uneven-aged forests of the Italian Alps

During the last millennia, all forests of the Italian Alps have been heavily affected by human land-use. Consequently, forest structures have been modified, and there are no old growth remains. In the last decades, however, many forests have been withdrawn from regular management, because wood production was unprofitable, and left to develop naturally. At the same time, in currently managed forests, silvicultural systems able to develop or maintain old-growth characteristics are being required. The aim of this paper was to assess the status and developmental dynamics of old-growth characteristics in mixed beech, silver fir, and Norway spruce montane forests of the eastern Italian Alps. We selected along a naturalness gradient (a) three old-growth forests in Bosnia and Montenegro (due to the lack of old-growth forests in the Italian Alps), (b) two forests withdrawn from regular management for at least 50 years, and (c) three currently managed forests. In each forest, we analysed 17 structural attributes, in order to assess their value as indicators of old-growth condition. Old-growth forests were characterized by significantly higher amounts of live and dead biomass, share of beech in the dominant and regeneration layers, and number of large trees. The diameter distribution was best described as a rotated sigmoid, differently from currently and formerly managed forest. We discuss the differences in old-growth characteristics across the management gradient and use our results to evaluate the effectiveness of retention prescriptions currently applied in the studied regions in maintaining or promoting old-growth structural attributes in managed forests

Effects of forest management on ground beetle diversity in alpine beech (Fagus sylvatica L.) stands

European beech forests are of particular importance for biodiversity, although relatively little is known about how beech forest management impacts on invertebrate communities. In this paper we investigated the influence of beech forest management history [i.e. over-mature coppices (OC) and coppices in conversion to high forests (CCHF)], climatic, topographic and microhabitat characteristics on ground beetle diversity (measured as total relative abundance, species richness, Shannon diversity and abundance of the endangered endemic species Carabus olympiae) in northern Italy. The diversity of forest specialist carabids was higher in OC and in forest stands characterized by a higher mean temperature and lower relative humidity. Moreover, we detected a positive response of several diversity variables to coarse wood debris cover or volume, herb cover, and the standard deviation of tree diameter. Currently, OC seems to be a more favorable habitat for forest carabids, including C. olympiae, although succession over time can lead to a progressive homogenization of the vegetation structure, with negative consequences for the conservation of the forest carabid assemblage.Based on our results, we suggest that the traditional management of beech coppice and its conversion to high forest be modified by including practices aimed at promoting structural and microhabitat diversity such as retention of large trees, creation of canopy gaps, retention of coarse wood debris and the preservation of 'islands' of older trees in the managed stands