Articulatory synthesis is based on modeling various physical phenomena of speech production, including sound radiation from the mouth. With regard to sound radiation, the most common approach is to ...approximate it in terms of a simple spherical source of strength equal to the mouth volume velocity. However, because this approximation is only valid at very low frequencies and does not account for the diffraction by the head and the torso, we simulated two alternative radiation characteristics that are potentially more realistic: the radiation from a vibrating piston in a spherical baffle, and the radiation from the mouth of a detailed model of the human head and torso. Using the articulatory speech synthesizer VocalTractLab, a corpus of 10 sentences was synthesized with the different radiation characteristics combined with three different phonation types. The synthesized sentences were acoustically compared with natural recordings of the same sentences in terms of their long-term average spectra (LTAS), and evaluated in terms of their naturalness and intelligibility. The intelligibility was not affected by the type of radiation characteristic. However, it was found that the more similar their LTAS was to real speech, the more natural the synthetic sentences were perceived to be. Hence, the naturalness was not directly determined by the realism of the radiation characteristic, but by the combined spectral effect of the radiation characteristic and the voice source. While the more realistic radiation models do not per se improve synthesis quality, they provide new insights in the study of speech production and articulatory synthesis.
•Computational simulation of vocal learning can be achieved without explicit speaker normalisation.•Deep-learning based speech recogniser provides better auditory guidance than acoustic features for ...learning articulatory targets.•Perception-guided vocal practice rather than phonetic imitation is therefore the likely strategy of vocal learning.•Coarticulatory dynamics are essential for learning CV syllables.•Using open-vocabulary dictation to evaluate model performance sets a new standard for vocal learning modelling.
It has long been a mystery how children learn to speak without formal instructions. Previous research has used computational modelling to help solve the mystery by simulating vocal learning with direct imitation or caregiver feedback, but has encountered difficulty in overcoming the speaker normalisation problem, namely, discrepancies between children’s vocalisations and that of adults due to age-related anatomical differences. Here we show that vocal learning can be successfully simulated via recognition-guided vocal exploration without explicit speaker normalisation. We trained an articulatory synthesiser with three-dimensional vocal tract models of an adult and two child configurations of different ages to learn monosyllabic English words consisting of CVC syllables, based on coarticulatory dynamics and two kinds of auditory feedback: (i) acoustic features to simulate universal phonetic perception (or direct imitation), and (ii) a deep-learning-based speech recogniser to simulate native-language phonological perception. Native listeners were invited to evaluate the learned synthetic speech with natural speech as baseline reference. Results show that the English words trained with the speech recogniser were more intelligible than those trained with acoustic features, sometimes close to natural speech. The successful simulation of vocal learning in this study suggests that a combination of coarticulatory dynamics and native-language phonological perception may be critical also for real-life vocal production learning.
This paper introduces a paradigm shift regarding vocal learning simulations, in which the communicative function of speech acquisition determines the learning process and intelligibility is ...considered the primary measure of learning success. Thereby, a novel approach for artificial vocal learning is presented that utilizes deep neural network-based phoneme recognition in order to calculate the speech acquisition objective function. This function guides a learning framework that involves the state-of-the-art articulatory speech synthesizer VocalTractLab as the motor-to-acoustic forward model. In this way, an extensive set of German phonemes, including most of the consonants and all stressed vowels, was produced successfully. The synthetic phonemes were rated as highly intelligible by human listeners. Furthermore, it is shown that visual speech information, such as lip and jaw movements, can be extracted from video recordings and be incorporated into the learning framework as an additional loss component during the optimization process. It was observed that this visual loss did not increase the overall intelligibility of phonemes. Instead, the visual loss acted as a regularization mechanism that facilitated the finding of more biologically plausible solutions in the articulatory domain.
The way infants use auditory cues to learn to speak despite the acoustic mismatch of their vocal apparatus is a hot topic of scientific debate. The simulation of early vocal learning using ...articulatory speech synthesis offers a way towards gaining a deeper understanding of this process. One of the crucial parameters in these simulations is the choice of features and a metric to evaluate the acoustic error between the synthesised sound and the reference target. We contribute with evaluating the performance of a set of 40 feature-metric combinations for the task of optimising the production of static vowels with a high-quality articulatory synthesiser. Towards this end we assess the usability of formant error and the projection of the feature-metric error surface in the normalised F1-F2 formant space. We show that this approach can be used to evaluate the impact of features and metrics and also to offer insight to perceptual results.
Disease manifestations in COVID-19 range from mild to severe illness associated with a dysregulated innate immune response. Alterations in function and regeneration of dendritic cells (DCs) and ...monocytes may contribute to immunopathology and influence adaptive immune responses in COVID-19 patients. We analyzed circulating DC and monocyte subsets in 65 hospitalized COVID-19 patients with mild/moderate or severe disease from acute illness to recovery and in healthy controls. Persisting reduction of all DC subpopulations was accompanied by an expansion of proliferating Lineage
−
HLADR
+
cells lacking DC markers. Increased frequency of CD163
+
CD14
+
cells within the recently discovered DC3 subpopulation in patients with more severe disease was associated with systemic inflammation, activated T follicular helper cells, and antibody-secreting cells. Persistent downregulation of CD86 and upregulation of programmed death-ligand 1 (PD-L1) in conventional DCs (cDC2 and DC3) and classical monocytes associated with a reduced capacity to stimulate naïve CD4
+
T cells correlated with disease severity. Long-lasting depletion and functional impairment of DCs and monocytes may have consequences for susceptibility to secondary infections and therapy of COVID-19 patients.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Alterations in white matter (WM) microstructure have been implicated in the pathophysiology of major depressive disorder (MDD). However, previous findings have been inconsistent, partially due to low ...statistical power and the heterogeneity of depression. In the largest multi-site study to date, we examined WM anisotropy and diffusivity in 1305 MDD patients and 1602 healthy controls (age range 12-88 years) from 20 samples worldwide, which included both adults and adolescents, within the MDD Working Group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium. Processing of diffusion tensor imaging (DTI) data and statistical analyses were harmonized across sites and effects were meta-analyzed across studies. We observed subtle, but widespread, lower fractional anisotropy (FA) in adult MDD patients compared with controls in 16 out of 25 WM tracts of interest (Cohen's d between 0.12 and 0.26). The largest differences were observed in the corpus callosum and corona radiata. Widespread higher radial diffusivity (RD) was also observed (all Cohen's d between 0.12 and 0.18). Findings appeared to be driven by patients with recurrent MDD and an adult age of onset of depression. White matter microstructural differences in a smaller sample of adolescent MDD patients and controls did not survive correction for multiple testing. In this coordinated and harmonized multisite DTI study, we showed subtle, but widespread differences in WM microstructure in adult MDD, which may suggest structural disconnectivity in MDD.
Disease manifestations in COVID-19 range from mild to severe illness associated with a dysregulated innate immune response. Alterations in function and regeneration of dendritic cells (DCs) and ...monocytes may contribute to immunopathology and influence adaptive immune responses in COVID-19 patients. We analyzed circulating DC and monocyte subsets in 65 hospitalized COVID-19 patients with mild/moderate or severe disease from acute illness to recovery and in healthy controls. Persisting reduction of all DC subpopulations was accompanied by an expansion of proliferating Lineage−HLADR+ cells lacking DC markers. Increased frequency of CD163+ CD14+ cells within the recently discovered DC3 subpopulation in patients with more severe disease was associated with systemic inflammation, activated T follicular helper cells, and antibody-secreting cells. Persistent downregulation of CD86 and upregulation of programmed death-ligand 1 (PD-L1) in conventional DCs (cDC2 and DC3) and classical monocytes associated with a reduced capacity to stimulate naïve CD4+ T cells correlated with disease severity. Long-lasting depletion and functional impairment of DCs and monocytes may have consequences for susceptibility to secondary infections and therapy of COVID-19 patients.
Author summary: Dendritic cells (DCs) recognize viral infections and trigger innate and adaptive antiviral immunity. COVID-19 severity is greatly influenced by the host immune response and modulation of DC generation and function after SARS-CoV-2 infection could play an important role in this disease. This study identifies a long-lasting reduction of DCs in the blood of COVID-19 patients and a functional impairment of these cells. Downregulation of costimulatory molecule CD86 and upregulation of inhibitory molecule PD-L1 in conventional DCs correlated with disease severity and were accompanied by a reduced ability to stimulate T cells. A higher frequency of CD163+ CD14+ cells in the DC3 subpopulation correlated with systemic inflammation suggesting that these cells may play a role in inflammatory responses of COVID-19 patients. Depletion and functional impairment of DCs beyond the acute phase of the disease may have consequences for susceptibility to secondary infections and clinical management of COVID-19 patients.
PDF
