22,574 research outputs found
Bio-inspired broad-class phonetic labelling
Recent studies have shown that the correct labeling of phonetic classes may help current Automatic Speech Recognition (ASR) when combined with classical parsing automata based on Hidden Markov Models (HMM).Through the present paper a method for Phonetic Class Labeling (PCL) based on bio-inspired speech processing is described. The methodology is based in the automatic detection of formants and formant trajectories after a careful separation of the vocal and glottal components of speech and in the operation of CF (Characteristic Frequency) neurons in the cochlear nucleus and cortical complex of the human auditory apparatus. Examples of phonetic class labeling are given and the applicability of the method to Speech Processing is discussed
Implementation Aspects of a Transmitted-Reference UWB Receiver
In this paper, we discuss the design issues of an ultra wide band (UWB) receiver targeting a single-chip CMOS implementation for low data-rate applications like ad hoc wireless sensor networks. A non-coherent transmitted reference (TR) receiver is chosen because of its small complexity compared to other architectures. After a brief recapitulation of the UWB fundamentals and a short discussion on the major differences between coherent and non-coherent receivers, we discuss issues, challenges and possible design solutions. Several simulation results obtained by means of a behavioral model are presented, together with an analysis of the trade-off between performance and complexity in an integrated circuit implementation
Resampling to accelerate cross-correlation searches for continuous gravitational waves from binary systems
Continuous-wave (CW) gravitational waves (GWs) call for
computationally-intensive methods. Low signal-to-noise ratio signals need
templated searches with long coherent integration times and thus fine
parameter-space resolution. Longer integration increases sensitivity. Low-mass
x-ray binaries (LMXBs) such as Scorpius X-1 (Sco X-1) may emit accretion-driven
CWs at strains reachable by current ground-based observatories. Binary orbital
parameters induce phase modulation. This paper describes how resampling
corrects binary and detector motion, yielding source-frame time series used for
cross-correlation. Compared to the previous, detector-frame, templated
cross-correlation method, used for Sco X-1 on data from the first Advanced LIGO
observing run (O1), resampling is about 20x faster in the costliest,
most-sensitive frequency bands. Speed-up factors depend on integration time and
search setup. The speed could be reinvested into longer integration with a
forecast sensitivity gain, 20 to 125 Hz median, of approximately 51%, or from
20 to 250 Hz, 11%, given the same per-band cost and setup. This paper's timing
model enables future setup optimization. Resampling scales well with longer
integration, and at 10x unoptimized cost could reach respectively 2.83x and
2.75x median sensitivities, limited by spin-wandering. Then an O1 search could
yield a marginalized-polarization upper limit reaching torque-balance at 100
Hz. Frequencies from 40 to 140 Hz might be probed in equal observing time with
2x improved detectors.Comment: 28 pages, 7 figures, 3 table
Tracking dynamic interactions between structural and functional connectivity : a TMS/EEG-dMRI study
Transcranial magnetic stimulation (TMS) in combination with neuroimaging techniques allows to measure the effects of a direct perturbation of the brain. When coupled with high-density electroencephalography (TMS/hd-EEG), TMS pulses revealed electrophysiological signatures of different cortical modules in health and disease. However, the neural underpinnings of these signatures remain unclear. Here, by applying multimodal analyses of cortical response to TMS recordings and diffusion magnetic resonance imaging (dMRI) tractography, we investigated the relationship between functional and structural features of different cortical modules in a cohort of awake healthy volunteers. For each subject, we computed directed functional connectivity interactions between cortical areas from the source-reconstructed TMS/hd-EEG recordings and correlated them with the correspondent structural connectivity matrix extracted from dMRI tractography, in three different frequency bands (alpha, beta, gamma) and two sites of stimulation (left precuneus and left premotor). Each stimulated area appeared to mainly respond to TMS by being functionally elicited in specific frequency bands, that is, beta for precuneus and gamma for premotor. We also observed a temporary decrease in the whole-brain correlation between directed functional connectivity and structural connectivity after TMS in all frequency bands. Notably, when focusing on the stimulated areas only, we found that the structure-function correlation significantly increases over time in the premotor area controlateral to TMS. Our study points out the importance of taking into account the major role played by different cortical oscillations when investigating the mechanisms for integration and segregation of information in the human brain
Optimal Source Tracking and Beaming of LISA
We revisit the directionally optimal data streams of LISA first introduced in
Nayak etal. It was shown that by using appropriate choice of Time delay
interferometric (TDI) combinations, a monochromatic fixed source in the
barycentric frame can be optimally tracked in the LISA frame. In this work, we
study the beaming properties of these optimal streams. We show that all the
three streams V+, Vx and Vo with maximum, minimum and zero directional SNR
respectively are highly beamed. We study in detail the frequency dependence of
the beaming.Comment: 8 pages, 9 figures. To appear in the proceedings of Sixth
International LISA Symposiu
Bio-inspired Dynamic Formant Tracking for Phonetic Labelling
It is a known fact that phonetic labeling may be relevant in helping current Automatic Speech Recognition (ASR) when combined with classical parsing systems as HMM's by reducing the search space. Through the present paper a method for Phonetic Broad-Class Labeling (PCL) based on speech perception in the high auditory centers is described. The methodology is based in the operation of CF (Characteristic Frequency) and FM (Frequency Modulation) neurons in the cochlear nucleus and cortical complex of the human auditory apparatus in the automatic detection of formants and formant dynamics on speech. Results obtained informant detection and dynamic formant tracking are given and the applicability of the method to Speech Processing is discussed
Sparse Automatic Differentiation for Large-Scale Computations Using Abstract Elementary Algebra
Most numerical solvers and libraries nowadays are implemented to use
mathematical models created with language-specific built-in data types (e.g.
real in Fortran or double in C) and their respective elementary algebra
implementations. However, built-in elementary algebra typically has limited
functionality and often restricts flexibility of mathematical models and
analysis types that can be applied to those models. To overcome this
limitation, a number of domain-specific languages with more feature-rich
built-in data types have been proposed. In this paper, we argue that if
numerical libraries and solvers are designed to use abstract elementary algebra
rather than language-specific built-in algebra, modern mainstream languages can
be as effective as any domain-specific language. We illustrate our ideas using
the example of sparse Jacobian matrix computation. We implement an automatic
differentiation method that takes advantage of sparse system structures and is
straightforward to parallelize in MPI setting. Furthermore, we show that the
computational cost scales linearly with the size of the system.Comment: Submitted to ACM Transactions on Mathematical Softwar
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