Articulatory feature classifiers trained on 2000 hours of telephone speech

The so-called tandem approach, where the posteriors of a multilayer perceptron (MLP) classifier are used as features in an automatic speech recognition (ASR) system has proven to be a very effective method. Most tandem approaches up to date have relied on MLPs trained for phone classification, and appended the posterior features to some standard feature hidden Markov model (HMM). In this paper, we develop an alternative tandem approach based on MLPs trained for articulatory feature (AF) classification. We also develop a factored observation model for characterizing the posterior and standard features at the HMM outputs, allowing for separate hidden mixture and state-tying structures for each factor. In experiments on a subset of Switchboard, we show that the AFbased tandem approach is as effective as the phone-based approach, and that the factored observation model significantly outperforms the simple feature concatenation approach while using fewer parameters

Early Changes in Tumor Perfusion from T1-Weighted Dynamic Contrast-Enhanced MRI following Neural Stem Cell-Mediated Therapy of Recurrent High-Grade Glioma Correlate with Overall Survival

Background. The aim of this study was to correlate T1-weighted dynamic contrast-enhanced MRI- (DCE-MRI-) derived perfusion parameters with overall survival of recurrent high-grade glioma patients who received neural stem cell- (NSC-) mediated enzyme/prodrug gene therapy. Methods. A total of 12 patients were included in this retrospective study. All patients were enrolled in a first-in-human study (NCT01172964) of NSC-mediated therapy for recurrent high-grade glioma. DCE-MRI data from all patients were collected and analyzed at three time points: MRI#1—day 1 postsurgery/treatment, MRI#2— day 7 ± 3 posttreatment, and MRI#3—one-month follow-up. Plasma volume (Vp), permeability (Ktr), and leakage (λtr) perfusion parameters were calculated by fitting a pharmacokinetic model to the DCE-MRI data. The contrast-enhancing (CE) volume was measured from the last dynamic phase acquired in the DCE sequence. Perfusion parameters and CE at each MRI time point were recorded along with their relative change between MRI#2 and MRI#3 (Δ32). Cox regression was used to analyze patient survival. Results. At MRI#1 and at MRI#3, none of the parameters showed a significant correlation with overall survival (OS). However, at MRI#2, CE and λtr were significantly associated with OS (p<0.05). The relative λtr and Vp from timepoint 2 to timepoint 3 (Δ32λtr and Δ32Vp) were each associated with a higher hazard ratio (p<0.05). All parameters were highly correlated, resulting in a multivariate model for OS including only CE at MRI#2 and Δ32Vp, with an R2 of 0.89. Conclusion. The change in perfusion parameter values from 1 week to 1 month following NSC-mediated therapy combined with contrast-enhancing volume may be a useful biomarker to predict overall survival in patients with recurrent high-grade glioma

Speech production knowledge in automatic speech recognition

Although much is known about how speech is produced, and research into speech production has resulted in measured articulatory data, feature systems of different kinds and numerous models, speech production knowledge is almost totally ignored in current mainstream approaches to automatic speech recognition. Representations of speech production allow simple explanations for many phenomena observed in speech which cannot be easily analyzed from either acoustic signal or phonetic transcription alone. In this article, we provide a survey of a growing body of work in which such representations are used to improve automatic speech recognition

Hypervelocity Impact of Unstressed and Stressed Titanium in a Whipple Configuration in Support of the Orion Crew Exploration Vehicle Service Module Propellant Tanks

Hypervelocity impacts were performed on six unstressed and six stressed titanium coupons with aluminium shielding in order to assess the effects of the partial penetration damage on the post impact micromechanical properties of titanium and on the residual strength after impact. This work is performed in support of the definition of the penetration criteria of the propellant tanks surfaces for the service module of the crew exploration vehicle where such a criterion is based on testing and analyses rather than on historical precedence. The objective of this work is to assess the effects of applied biaxial stress on the damage dynamics and morphology. The crater statistics revealed minute differences between stressed and unstressed coupon damage. The post impact residual stress analyses showed that the titanium strength properties were generally unchanged for the unstressed coupons when compared with undamaged titanium. However, high localized strains were shown near the craters during the tensile tests

Factors associated with crisis pregnancies in Ireland: Findings from three nationally representative sexual health surveys

Background: Findings on the demographic and sexual health characteristics associated with the experience of a crisis pregnancy is important to inform the public health policy of a country, including Ireland. Findings from other jurisdictions have suggested that certain demographic groups are at risk for unintended pregnancies and the disparity between the groups have been growing in recent years. Ireland is a country which experienced much economic and societal change in the first decade of the 21st century, changes which are likely to have affected demographic variables pertaining to sexual health. The current study had two aims: to investigate changes in the socioeconomic characteristics associated with crisis pregnancies over a seven year period [2003 to 2010], and to investigate the recent [2010] socioeconomic risk factors associated with crisis pregnancies in Ireland. Methods: The study compared the results from 18-45 year old women using data from three broadly similar nationally representative Irish sexual health surveys carried out in 2003, 2004-2006 and 2010. Chi square analysis compared of the socioeconomic characteristics across the seven year period and found that a higher proportion of women with two or more children and women for whom religion was not important reported a crisis pregnancy in 2010 compared with earlier years. A logistic regression then investigated the sexual health history and socioeconomic factors associated with the experience of a recent crisis pregnancy using the most recent 2010 data. Results: Receipt of sex education and contraception use at first sex significantly predicted the experiencing of a recent crisis pregnancy. Younger women and those with a lower level of education were more likely to report having experienced a recent crisis pregnancy. Conclusion: Similar demographic groups are at risk for experiencing a crisis pregnancy in Ireland compared with international research, yet the disparities between demographic groups who have experienced a crisis pregnancy appear to be decreasing rather than increasing over a seven year period. Recommendations are made with regard to the provision of continued sex education throughout the lifespan, particularly for those women who are at an increased risk of experiencing a crisis pregnancy

Manual transcription of conversational speech at the articulatory feature level

Although much is known about how speech is produced, and research into speech production has resulted in measured articulatory data, feature systems of different kinds and numerous models, speech production knowledge is almost totally ignored in current mainstream approaches to automatic speech recognition. Representations of speech production allow simple explanations for many phenomena observed in speech which cannot be easily analyzed from either acoustic signal or phonetic transcription alone. In this article, we provide a survey of a growing body of work in which such representations are used to improve automatic speech recognition

EIFiso4G augments the synthesis of specific plant proteins involved in normal chloroplast function

Copyright © 2019 American Society of Plant Biologists. All rights reserved. The plant-specific translation initiation complex eIFiso4F is encoded by three genes in Arabidopsis (Arabidopsis thaliana)-genes encoding the cap binding protein eIFiso4E (eifiso4e) and two isoforms of the large subunit scaffolding protein eIFiso4G (i4g1 and i4g2). To quantitate phenotypic changes, a phenomics platform was used to grow wild-type and mutant plants (i4g1, i4g2, i4e, i4g1 × i4g2, and i4g1 × i4g2 × i4e [i4f]) under various light conditions. Mutants lacking both eIFiso4G isoforms showed the most obvious phenotypic differences from the wild type. Two-dimensional differential gel electrophoresis and mass spectrometry were used to identify changes in protein levels in plants lacking eIFiso4G. Four of the proteins identified as measurably decreased and validated by immunoblot analysis were two light harvesting complex binding proteins 1 and 3, Rubisco activase, and carbonic anhydrase. The observed decreased levels for these proteins were not the direct result of decreased transcription or protein instability. Chlorophyll fluorescence induction experiments indicated altered quinone reduction kinetics for the double and triple mutant plants with significant differences observed for absorbance, trapping, and electron transport. Transmission electron microscopy analysis of the chloroplasts in mutant plants showed impaired grana stacking and increased accumulation of starch granules consistent with some chloroplast proteins being decreased. Rescue of the i4g1 × i4g2 plant growth phenotype and increased expression of the validated proteins to wild-type levels was obtained by overexpression of eIFiso4G1. These data suggest a direct and specialized role for eIFiso4G in the synthesis of a subset of plant proteins

Articulatory feature-based methods for acoustic and audio-visual speech recognition: Summary from the 2006 JHU Summer Workshop.

We report on investigations, conducted at the 2006 Johns HopkinsWorkshop, into the use of articulatory features (AFs) for observation and pronunciation models in speech recognition. In the area of observation modeling, we use the outputs of AF classiers both directly, in an extension of hybrid HMM/neural network models, and as part of the observation vector, an extension of the tandem approach. In the area of pronunciation modeling, we investigate a model having multiple streams of AF states with soft synchrony constraints, for both audio-only and audio-visual recognition. The models are implemented as dynamic Bayesian networks, and tested on tasks from the Small-Vocabulary Switchboard (SVitchboard) corpus and the CUAVE audio-visual digits corpus. Finally, we analyze AF classication and forced alignment using a newly collected set of feature-level manual transcriptions