Investigating the Effects of Word Substitution Errors on Sentence Embeddings

A key initial step in several natural language processing (NLP) tasks involves embedding phrases of text to vectors of real numbers that preserve semantic meaning. To that end, several methods have been recently proposed with impressive results on semantic similarity tasks. However, all of these approaches assume that perfect transcripts are available when generating the embeddings. While this is a reasonable assumption for analysis of written text, it is limiting for analysis of transcribed text. In this paper we investigate the effects of word substitution errors, such as those coming from automatic speech recognition errors (ASR), on several state-of-the-art sentence embedding methods. To do this, we propose a new simulator that allows the experimenter to induce ASR-plausible word substitution errors in a corpus at a desired word error rate. We use this simulator to evaluate the robustness of several sentence embedding methods. Our results show that pre-trained neural sentence encoders are both robust to ASR errors and perform well on textual similarity tasks after errors are introduced. Meanwhile, unweighted averages of word vectors perform well with perfect transcriptions, but their performance degrades rapidly on textual similarity tasks for text with word substitution errors.Comment: 4 Pages, 2 figures. Copyright IEEE 2019. Accepted and to appear in the Proceedings of the 44th International Conference on Acoustics, Speech, and Signal Processing 2019 (IEEE-ICASSP-2019), May 12-17 in Brighton, U.K. Personal use of this material is permitted. However, permission to reprint/republish this material must be obtained from the IEE

Crystallization of a quasi-two-dimensional granular fluid

We experimentally investigate the crystallization of a uniformly heated quasi-2D granular fluid as a function of filling fraction. Our experimental results for the Lindemann melting criterion, the radial distribution function, the bond order parameter and the statistics of topological changes at the particle level are the same as those found in simulations of equilibrium hard disks. This direct mapping suggests that the study of equilibrium systems can be effectively applied to study non-equilibrium steady states like those found in our driven and dissipative granular system.Comment: 4 pages, 4 figures, submitted to Phys. Rev. Let

Implications of precision measurements on texture specific fermion mass matrices

Implications of texture specific mass matrices have been investigated for both quarks and neutrinos. Interestingly, for the case of quarks Fritzsch-like texture 4 zero mass matrices have been found to be compatible with the present precisely known sin2\beta as well as other precise CKM matrix elements. In the case of leptonic mass matrices, for both Majorana and Dirac neutrinos we find that for texture 4, 5, 6 zero mass matrices the inverted hierarchy and degenerate scenarios of neutrino masses are ruled out by the present data.Comment: 8 pages, 1 figur

Near Infrared Spectroscopic Monitoring During Cardiopulmonary Exercise Testing Detects Anaerobic Threshold

Cardiopulmonary exercise testing (CPET) provides assessment of the integrative responses involving the pulmonary, cardiovascular, and skeletal muscle systems. Application of exercise testing remains limited to children who are able to understand and cooperate with the exercise protocol. Near-infrared spectroscopy (NIRS) provides a noninvasive, continuous method to monitor regional tissue oxygenation (rSO2). Our specific aim was to predict anaerobic threshold (AT) during CPET noninvasively using two-site NIRS monitoring. Achievement of a practical noninvasive technology for estimating AT will increase the compatibility of CPET. Patients without structural or acquired heart disease were eligible for inclusion if they were ordered to undergo CPET by a cardiologist. Data from 51 subjects was analyzed. The ventilatory anaerobic threshold (VAT) was computed on VCO2 and respiratory quotient post hoc using the standard V-slope method. The inflection points of the regional rSO2 time-series were identified as the noninvasive regional NIRS AT for each of the two monitored regions (cerebral and kidney). AT calculation made using an average of kidney and brain NIRS matched the calculation made by VAT for the same patient. Two-site NIRS monitoring of visceral organs is a predictor of AT

Reviewing the Government's Numbers on Regulation

This paper has two objectives: first, to provide more information on the data used to construct a controversial economic analysis published by the Joint Center that makes use of over 100 government regulatory impact analyses; and second, to provide further sensitivity analysis of key variables in that study. A key finding of this paper is that the results of the earlier analysis of government regulatory impact analyses appear to be fairly robust within the data set that was constructed. We offer the following conclusions. First, aggregate net benefits for final regulations are positive under a wide variety of assumptions. Second, a substantial number of final regulations do not pass a benefit-cost test under a wide variety of assumptions. By rejecting at least some of these regulations, government could have increased aggregate net social benefits. Third, aggregate net benefits exhibit a wide range across regulations. And fourth, agencies should improve the quality of their regulatory impact analyses. Also of interest from the Joint Center: The Economic Analysis of Regulation: A Response to the Critics Robert W. Hahn

ON THE LOG PERIODOGRAM REGRESSION ESTIMATOR OF THE MEMORY PARAMETER IN LONG MEMORY STOCHASTIC VOLATILITY MODELS

We consider semiparametric estimation of the memory parameter in a long memory stochastic volatility model. We study the estimator based on a log periodogram regression as originally proposed by Geweke and Porter-Hudak (1983, Journal of Time Series Analysis 4, 221âÃÂÃÂ238). Expressions for the asymptotic bias and variance of the estimator are obtained, and the asymptotic distribution is shown to be the same as that obtained in recent literature for a Gaussian long memory series. The theoretical result does not require omission of a block of frequencies near the origin. We show that this ability to use the lowest frequencies is particularly desirable in the context of the long memory stochastic volatility model.Statistics Working Papers Serie