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We focus on developing an account of user behavior under error conditions, working with annotated data from real human-machine mixed initiative dialogs. In particular, we examine categories of error perception, user behavior under error, effect of user strategies on error recovery, and the role of user initiative in error situations. A conditional(More)
The purpose of this study was to examine the reliability and validity of curriculum-based measures as indicator of growth in content-area learning. Participants were 58 students in 2 seventh-grade social studies classes. CBM measures were student- and administrator-read vocabulary-matching probes. Criterion measures were performance on a knowledge test, the(More)
Overview This chapter describes Individual Growth and Development Indicators for preschool-aged children. Preschool Individual Growth and Development Indicators (or IGDIs) are quick, efficient, and repeatable measures of correlates or components of developmental performance designed for use with children 30 to 66 months of age. Preschool IGDIs sample child(More)
The paper address user behavior modeling in a machinemediated setting involving bidirectional speech translation. Specifically, usability data from doctor-patient dialogs involving a two way English-Persian speech translation system are analyzed to understand the nature, and extent, of user accommodation to machine errors. We consider user type "categorized(More)
In this paper we describe the English-Persian speech to speech translation device, and provide insight on the lessons learned during the first phase of development of this system. We start by giving an overview of the underlying components of the device: the front end ASR, the machine translation system and the speech generation system. Challenges such as(More)
Educational performance based on the learning outcomes of formal schooling in a future knowledge society could be significantly different from that of today. This study investigates the possibilities of developing an educational performance indicator for new-millennium learners (NMLs). The researchers conducted literature reviews, a meeting of experts,(More)
We investigate factors related to interfacing a speech-to-speech translation device with multimodal capabilities. We evaluate the efficacy of the interactions using a measure for meaning transfer, we call concept score. We show that employing a multimodal interface improves translation quality, in this study, by 24%. We also show that while some users(More)
The study provides an empirical analysis of long-term user behavioral changes and varying user strategies during cross-lingual interaction using the multimodal speech-to-speech (S2S) translation system of USC/SAIL. The goal is to inform user adaptive designs of such systems. A 4-week medical-scenario-based study provides the basis for our analysis. The data(More)
—Our hypothesis is that the video game industry, in the attempt to simulate a realistic experience, has inadvertently collected very accurate data which can be used to solve problems in the real world. In this paper we describe a novel approach to soccer match prediction that makes use of only virtual data collected from a video game(FIFA 2015). Our results(More)