The Inverse Amplitude Method and Adler Zeros

The Inverse Amplitude Method is a powerful unitarization technique to enlarge the energy applicability region of Effective Lagrangians. It has been widely used to describe resonances from Chiral Perturbation Theory as well as for the Strongly Interacting Symmetry Breaking Sector. In this work we show how it can be slightly modified to account also for the sub-threshold region, incorporating correctly the Adler zeros required by chiral symmetry and eliminating spurious poles. These improvements produce negligible effects on the physical region.Comment: 17 pages, 4 figure

Three-Body Dynamics and Self-Powering of an Electrodynamic Tether in a Plasmasphere

The dynamics of an electrodynamic tether in a three-body gravitational environment are investigated. In the classical two-body scenario the extraction of power is at the expense of orbital kinetic energy. As a result of power extraction, an electrodynamic tether satellite system loses altitude and deorbits. This concept has been proposed and well investigated in the past, for example for orbital debris mitigation and spent stages reentry. On the other hand, in the three-body scenario an electrodynamic tether can be placed in an equilibrium position fixed with respect to the two primary bodies without deorbiting, and at the same time generate power for onboard use. The appearance of new equilibrium positions in the perturbed three-body problem allow this to happen as the electrical power is extracted at the expenses of the plasma corotating with the primary body. Fundamental differences between the classical twobody dynamics and the new phenomena appearing in the circular restricted three-body problem perturbed by the electrodynamic force of the electrodynamic tether are shown in the paper. An interesting application of an electrodynamic tether placed in the Jupiter plasma torus is then considered, in which the electrodynamic tether generates useful electrical power of about 1 kW with a 20-km-long electrodynamic tether from the environmental plasma without losing orbital energy

A Comparison of Front-Ends for Bitstream-Based ASR over IP

Automatic speech recognition (ASR) is called to play a relevant role in the provision of spoken interfaces for IP-based applications. However, as a consequence of the transit of the speech signal over these particular networks, ASR systems need to face two new challenges: the impoverishment of the speech quality due to the compression needed to fit the channel capacity and the inevitable occurrence of packet losses. In this framework, bitstream-based approaches that obtain the ASR feature vectors directly from the coded bitstream, avoiding the speech decoding process, have been proposed ([S.H. Choi, H.K. Kim, H.S. Lee, Speech recognition using quantized LSP parameters and their transformations in digital communications, Speech Commun. 30 (4) (2000) 223–233. A. Gallardo-Antolín, C. Pelàez-Moreno, F. Díaz-de-María, Recognizing GSM digital speech, IEEE Trans. Speech Audio Process., to appear. H.K. Kim, R.V. Cox, R.C. Rose, Performance improvement of a bitstream-based front-end for wireless speech recognition in adverse environments, IEEE Trans. Speech Audio Process. 10 (8) (2002) 591–604. C. Peláez-Moreno, A. Gallardo-Antolín, F. Díaz-de-María, Recognizing voice over IP networks: a robust front-end for speech recognition on the WWW, IEEE Trans. Multimedia 3(2) (2001) 209–218], among others) to improve the robustness of ASR systems. LSP (Line Spectral Pairs) are the preferred set of parameters for the description of the speech spectral envelope in most of the modern speech coders. Nevertheless, LSP have proved to be unsuitable for ASR, and they must be transformed into cepstrum-type parameters. In this paper we comparatively evaluate the robustness of the most significant LSP to cepstrum transformations in a simulated VoIP (voice over IP) environment which includes two of the most popular codecs used in that network (G.723.1 and G.729) and several network conditions. In particular, we compare ‘pseudocepstrum’ [H.K. Kim, S.H. Choi, H.S. Lee, On approximating Line Spectral Frequencies to LPC cepstral coefficients, IEEE Trans. Speech Audio Process. 8 (2) (2000) 195–199], an approximated but straightforward transformation of LSP into LP cepstral coefficients, with a more computationally demanding but exact one. Our results show that pseudocepstrum is preferable when network conditions are good or computational resources low, while the exact procedure is recommended when network conditions become more adverse.Publicad

Composite and elementary natures of a1(1260) meson

We develop a practical method to analyze the mixing structure of hadrons consisting of two components of quark-composite and hadronic composite. As an example we investigate the properties of the axial vector meson a1(1260) and discuss its mixing properties quantitatively. We also make reference to the large Nc procedure and its limitation for the classification of such a mixed state.Comment: 13 pages, 4 figure

A Speech Recognizer based on Multiclass SVMs with HMM-Guided Segmentation

Automatic Speech Recognition (ASR) is essentially a problem of pattern classification, however, the time dimension of the speech signal has prevented to pose ASR as a simple static classification problem. Support Vector Machine (SVM) classifiers could provide an appropriate solution, since they are very well adapted to high-dimensional classification problems. Nevertheless, the use of SVMs for ASR is by no means straightforward, mainly because SVM classifiers require an input of fixed-dimension. In this paper we study the use of a HMM-based segmentation as a mean to get the fixed-dimension input vectors required by SVMs, in a problem of isolated-digit recognition. Different configurations for all the parameters involved have been tested. Also, we deal with the problem of multi-class classification (as SVMs are initially binary classifers), studying two of the most popular approaches: 1-vs-all and 1-vs-1

Jovian Capture of a Spacecraft with a Self-Balanced Electrodynamic Bare Tether

This paper proposes and analyzes the use of a nonrotating tethered system for a direct capture in Jovian orbit using the electrodynamic force generated along the cable. A detailed dynamical model is developed showing a strong gravitational and electrodynamic coupling between the center of mass and the attitude motions. This paper shows the feasibility of a direct capture in Jovian orbit of a rigid tethered system preventing the tether from rotating. Additional mechanical–thermal requirements are explored, and preliminary operational limits are defined to complete the maneuver. In particular, to ensure that the system remains nonrotating, a nominal attitude profile for a self-balanced electrodynamic tether is proposed, as well as a simple feedback control

SVMs for Automatic Speech Recognition: a Survey

Hidden Markov Models (HMMs) are, undoubtedly, the most employed core technique for Automatic Speech Recognition (ASR). Nevertheless, we are still far from achieving high-performance ASR systems. Some alternative approaches, most of them based on Artificial Neural Networks (ANNs), were proposed during the late eighties and early nineties. Some of them tackled the ASR problem using predictive ANNs, while others proposed hybrid HMM/ANN systems. However, despite some achievements, nowadays, the preponderance of Markov Models is a fact. During the last decade, however, a new tool appeared in the field of machine learning that has proved to be able to cope with hard classification problems in several fields of application: the Support Vector Machines (SVMs). The SVMs are effective discriminative classifiers with several outstanding characteristics, namely: their solution is that with maximum margin; they are capable to deal with samples of a very higher dimensionality; and their convergence to the minimum of the associated cost function is guaranteed. These characteristics have made SVMs very popular and successful. In this chapter we discuss their strengths and weakness in the ASR context and make a review of the current state-of-the-art techniques. We organize the contributions in two parts: isolated-word recognition and continuous speech recognition. Within the first part we review several techniques to produce the fixed-dimension vectors needed for original SVMs. Afterwards we explore more sophisticated techniques based on the use of kernels capable to deal with sequences of different length. Among them is the DTAK kernel, simple and effective, which rescues an old technique of speech recognition: Dynamic Time Warping (DTW). Within the second part, we describe some recent approaches to tackle more complex tasks like connected digit recognition or continuous speech recognition using SVMs. Finally we draw some conclusions and outline several ongoing lines of research

Chiral Perturbation Theory, the 1/Nc{1/N_c} expansion and Regge behaviour determine the structure of the lightest scalar meson

The leading $1/N_c$ behaviour of Unitarised Chiral Perturbation Theory distinguishes the nature of the $\rho$ and the $\sigma$. At one loop order the $\rho$ is a ${\bar q}q$ meson, while the $\sigma$ is not. However, semi-local duality between resonances and Regge behaviour cannot be satisfied for larger $N_c$, if such a distinction holds. While the $\sigma$ at $N_c=3$ is inevitably dominated by its di-pion component, Unitarised Chiral Perturbation Theory beyond one loop order reveals that as $N_c$ increases above 6-8, the $\sigma$ has a sub-dominant ${\bar q}q$ fraction up at 1.2 GeV. Remarkably this ensures semi-local duality is fulfilled for the range of $N_c \lesssim 15$, where the unitarisation procedure adopted applies.Comment: 22 pages, 8 figures. Version to be published in Physical Review