Combination strategy based on relative performance monitoring for multi-stream reverberant speech recognition

A multi-stream framework with deep neural network (DNN) classifiers is applied to improve automatic speech recognition (ASR) in environments with different reverberation characteristics. We propose a room parameter estimation model to establish a reliable combination strategy which performs on either DNN posterior probabilities or word lattices. The model is implemented by training a multilayer perceptron incorporating auditory-inspired features in order to distinguish between and generalize to various reverberant conditions, and the model output is shown to be highly correlated to ASR performances between multiple streams, i.e., relative performance monitoring, in contrast to conventional mean temporal distance based performance monitoring for a single stream. Compared to traditional multi-condition training, average relative word error rate improvements of 7.7% and 9.4% have been achieved by the proposed combination strategies performing on posteriors and lattices, respectively, when the multi-stream ASR is tested in known and unknown simulated reverberant environments as well as realistically recorded conditions taken from REVERB Challenge evaluation set

Exploring auditory-inspired acoustic features for room acoustic parameter estimation from monaural speech

Room acoustic parameters that characterize acoustic environments can help to improve signal enhancement algorithms such as for dereverberation, or automatic speech recognition by adapting models to the current parameter set. The reverberation time (RT) and the early-to-late reverberation ratio (ELR) are two key parameters. In this paper, we propose a blind ROom Parameter Estimator (ROPE) based on an artificial neural network that learns the mapping to discrete ranges of the RT and the ELR from single-microphone speech signals. Auditory-inspired acoustic features are used as neural network input, which are generated by a temporal modulation filter bank applied to the speech time-frequency representation. ROPE performance is analyzed in various reverberant environments in both clean and noisy conditions for both fullband and subband RT and ELR estimations. The importance of specific temporal modulation frequencies is analyzed by evaluating the contribution of individual filters to the ROPE performance. Experimental results show that ROPE is robust against different variations caused by room impulse responses (measured versus simulated), mismatched noise levels, and speech variability reflected through different corpora. Compared to state-of-the-art algorithms that were tested in the acoustic characterisation of environments (ACE) challenge, the ROPE model is the only one that is among the best for all individual tasks (RT and ELR estimation from fullband and subband signals). Improved fullband estimations are even obtained by ROPE when integrating speech-related frequency subbands. Furthermore, the model requires the least computational resources with a real time factor that is at least two times faster than competing algorithms. Results are achieved with an average observation window of 3 s, which is important for real-time applications

Joint estimation of reverberation time and early-to-late reverberation ratio from single-channel speech signals

The reverberation time (RT) and the early-to-late reverberation ratio (ELR) are two key parameters commonly used to characterize acoustic room environments. In contrast to conventional blind estimation methods that process the two parameters separately, we propose a model for joint estimation to predict the RT and the ELR simultaneously from single-channel speech signals from either full-band or sub-band frequency data, which is referred to as joint room parameter estimator (jROPE). An artificial neural network is employed to learn the mapping from acoustic observations to the RT and the ELR classes. Auditory-inspired acoustic features obtained by temporal modulation filtering of the speech time-frequency representations are used as input for the neural network. Based on an in-depth analysis of the dependency between the RT and the ELR, a two-dimensional (RT, ELR) distribution with constrained boundaries is derived, which is then exploited to evaluate four different configurations for jROPE. Experimental results show that-in comparison to the single-task ROPE system which individually estimates the RT or the ELR-jROPE provides improved results for both tasks in various reverberant and (diffuse) noisy environments. Among the four proposed joint types, the one incorporating multi-task learning with shared input and hidden layers yields the best estimation accuracies on average. When encountering extreme reverberant conditions with RTs and ELRs lying beyond the derived (RT, ELR) distribution, the type considering RT and ELR as a joint parameter performs robustly, in particular. From state-of-the-art algorithms that were tested in the acoustic characterization of environments challenge, jROPE achieves comparable results among the best for all individual tasks (RT and ELR estimation from full-band and sub-band signals)

Análise técnico-econômica comparativa das tecnologias de concentração heliotérmica em localidades brasileiras

CIES2020 - XVII Congresso Ibérico e XIII Congresso Ibero-americano de Energia SolarRESUMO: A avaliação da viabilidade econômica de novos empreendimentos é uma etapa indispensável no planejamento e na discussão de políticas energéticas. Diante disso, este estudo aborda uma análise técnico-econômica das principais tecnologias utilizadas em projetos CSP por meio de simulações computacionais de plantas em 20 localidades brasileiras. As usinas são modeladas em dois cenários de potência instalada (50 e 125 MWe) e capacidade do sistema de armazenamento de energia térmica (7 e 12 horas). Os parâmetros utilizados na comparação entre os diferentes cenários, localidades e tecnologias são LCOE, geração de eletricidade, área do campo solar, Múltiplo Solar, CAPEX e OPEX nivelado. De maneira geral, esses parâmetros sugerem que a tecnologia de torre apresenta vantagens para maiores escalas de operação, enquanto a de cilindro é mais indicada para plantas de menor capacidade. Por possuir os mais baixos valores de CAPEX para plantas de pequeno porte, a alternativa de Fresnel é atrativa na inserção de projetos piloto em países com desenvolvimento incipiente da tecnologia CSP, situação na qual se enquadra o Brasil.ABSTRACT: Assessing the economic viability of new ventures is an essential activity in energy planning and energy policy discussion. In this context, this paper approaches a technical economic analysis of the main CSP technologies used worldwide through numerical simulations in 20 Brazilian sites using the software System Advisor Model. Power plants were designed in two scenarios of capacity and TES capacity: the first with 50 MWe capacity and 7 hours of equivalent storage, and the second with 125 MWe and 12 hours of storage. The parameters used in the comparison between the different scenarios, locations and technologies were LCOE, annual electricity output, solar field area, Solar Multiple, CAPEX and levelized OPEX, which broadly suggested Power Tower has greater competitive advantages for a larger scale operation, while Parabolic Trough Collectors are more suitable for plants with lower installed capacity. Because it has the lowest Capital Costs up to a given solar field area, Fresnel alternative is attractive in the insertion of small scale CSP power plants in countries with undeveloped CSP technology, e.g. Brazil.info:eu-repo/semantics/publishedVersio

The Primordial Inflation Explorer (PIXIE): A Nulling Polarimeter for Cosmic Microwave Background Observations

The Primordial Inflation Explorer (PIXIE) is an Explorer-class mission to measure the gravity-wave signature of primordial inflation through its distinctive imprint on the linear polarization of the cosmic microwave background. The instrument consists of a polarizing Michelson interferometer configured as a nulling polarimeter to measure the difference spectrum between orthogonal linear polarizations from two co-aligned beams. Either input can view the sky or a temperature-controlled absolute reference blackbody calibrator. PIXIE will map the absolute intensity and linear polarization (Stokes I, Q, and U parameters) over the full sky in 400 spectral channels spanning 2.5 decades in frequency from 30 GHz to 6 THz (1 cm to 50 um wavelength). Multi-moded optics provide background-limited sensitivity using only 4 detectors, while the highly symmetric design and multiple signal modulations provide robust rejection of potential systematic errors. The principal science goal is the detection and characterization of linear polarization from an inflationary epoch in the early universe, with tensor-to-scalar ratio r < 10^{-3} at 5 standard deviations. The rich PIXIE data set will also constrain physical processes ranging from Big Bang cosmology to the nature of the first stars to physical conditions within the interstellar medium of the Galaxy.Comment: 37 pages including 17 figures. Submitted to the Journal of Cosmology and Astroparticle Physic

Love and limblessness: male heterosexuality, disability, and the Great War

Tens of thousands of British men were permanently wounded as a result of war service. Their return home sparked debates about the wounded male body, female accountability for war-injuries, and the ideology, performance, and practice of masculinity. Other historians have shown how ‘broken heroes’ from the First World War were constituted into ‘men’ in four contexts: physical appearance, occupation, sport, and Britishness. This article explores a fifth dimension: sexuality. It explores debates about the need for war-disabled men to establish stable marital relationships and investigates some attempts to encourage this, including encouraging women to take the initiative in proposing marriage and the establishment of The League for the Marrying of Broken Heroes

Solar Wind Turbulence and the Role of Ion Instabilities

International audienc

Functional diversity of chemokines and chemokine receptors in response to viral infection of the central nervous system.

Encounters with neurotropic viruses result in varied outcomes ranging from encephalitis, paralytic poliomyelitis or other serious consequences to relatively benign infection. One of the principal factors that control the outcome of infection is the localized tissue response and subsequent immune response directed against the invading toxic agent. It is the role of the immune system to contain and control the spread of virus infection in the central nervous system (CNS), and paradoxically, this response may also be pathologic. Chemokines are potent proinflammatory molecules whose expression within virally infected tissues is often associated with protection and/or pathology which correlates with migration and accumulation of immune cells. Indeed, studies with a neurotropic murine coronavirus, mouse hepatitis virus (MHV), have provided important insight into the functional roles of chemokines and chemokine receptors in participating in various aspects of host defense as well as disease development within the CNS. This chapter will highlight recent discoveries that have provided insight into the diverse biologic roles of chemokines and their receptors in coordinating immune responses following viral infection of the CNS

FGF receptor genes and breast cancer susceptibility: results from the Breast Cancer Association Consortium

Background:Breast cancer is one of the most common malignancies in women. Genome-wide association studies have identified FGFR2 as a breast cancer susceptibility gene. Common variation in other fibroblast growth factor (FGF) receptors might also modify risk. We tested this hypothesis by studying genotyped single-nucleotide polymorphisms (SNPs) and imputed SNPs in FGFR1, FGFR3, FGFR4 and FGFRL1 in the Breast Cancer Association Consortium. Methods:Data were combined from 49 studies, including 53 835 cases and 50 156 controls, of which 89 050 (46 450 cases and 42 600 controls) were of European ancestry, 12 893 (6269 cases and 6624 controls) of Asian and 2048 (1116 cases and 932 controls) of African ancestry. Associations with risk of breast cancer, overall and by disease sub-type, were assessed using unconditional logistic regression. Results:Little evidence of association with breast cancer risk was observed for SNPs in the FGF receptor genes. The strongest evidence in European women was for rs743682 in FGFR3; the estimated per-allele odds ratio was 1.05 (95 confidence interval=1.02-1.09, P=0.0020), which is substantially lower than that observed for SNPs in FGFR2. Conclusion:Our results suggest that common variants in the other FGF receptors are not associated with risk of breast cancer to the degree observed for FGFR2. © 2014 Cancer Research UK

Time-integrated luminosity recorded by the BABAR detector at the PEP-II e+e- collider

This article is the Preprint version of the final published artcile which can be accessed at the link below.We describe a measurement of the time-integrated luminosity of the data collected by the BABAR experiment at the PEP-II asymmetric-energy e+e- collider at the ϒ(4S), ϒ(3S), and ϒ(2S) resonances and in a continuum region below each resonance. We measure the time-integrated luminosity by counting e+e-→e+e- and (for the ϒ(4S) only) e+e-→μ+μ- candidate events, allowing additional photons in the final state. We use data-corrected simulation to determine the cross-sections and reconstruction efficiencies for these processes, as well as the major backgrounds. Due to the large cross-sections of e+e-→e+e- and e+e-→μ+μ-, the statistical uncertainties of the measurement are substantially smaller than the systematic uncertainties. The dominant systematic uncertainties are due to observed differences between data and simulation, as well as uncertainties on the cross-sections. For data collected on the ϒ(3S) and ϒ(2S) resonances, an additional uncertainty arises due to ϒ→e+e-X background. For data collected off the ϒ resonances, we estimate an additional uncertainty due to time dependent efficiency variations, which can affect the short off-resonance runs. The relative uncertainties on the luminosities of the on-resonance (off-resonance) samples are 0.43% (0.43%) for the ϒ(4S), 0.58% (0.72%) for the ϒ(3S), and 0.68% (0.88%) for the ϒ(2S).This work is supported by the US Department of Energy and National Science Foundation, the Natural Sciences and Engineering Research Council (Canada), the Commissariat à l’Energie Atomique and Institut National de Physique Nucléaire et de Physiquedes Particules (France), the Bundesministerium für Bildung und Forschung and Deutsche Forschungsgemeinschaft (Germany), the Istituto Nazionale di Fisica Nucleare (Italy), the Foundation for Fundamental Research on Matter (The Netherlands), the Research Council of Norway, the Ministry of Education and Science of the Russian Federation, Ministerio de Ciencia e Innovación (Spain), and the Science and Technology Facilities Council (United Kingdom). Individuals have received support from the Marie-Curie IEF program (European Union) and the A.P. Sloan Foundation (USA)