We report three experiments comparing con®dence judgments made by actors and by observers. In Experiment 1, actors generated qualitative answers (countries of the world) in a country-identi®cation task; in Experiment 2, actors generated quantitative answers (years) in a historical event-dating task. Both actors and observers indicated their con®dence in the actors' answers. Actors were signi®ca...

The Maximum a posteriori hypothesis is treated as the decoded truth in speech recognition. However, since the word recognition accuracy is not 100%, it is desirable to have an independent con dence measure on how good the maximum a posteriori hypothesis is relative to the spoken truth for some applications. E orts are in progress [1, 2, 3] to develop such con dence measures with the intent of a...

We study the problem of measuring the uncertainty of computable general equilibrium (CGE) (or RBC)-type model simulations associated with parameter uncertainty. We describe two approaches for building conŽ dence sets on model endogenous variables. The Ž rst uses a standard Wald-type statistic. The second approach assumes that a conŽ dence set (sampling or Baycsian) is available for the free par...

This paper describes our approach to the estimation of con dence in the words generated by a speech recognition system. We describe the models and the features employed for con dence estimation. In addition we discuss the characteristics of an information-theoretic metric for assessing the performance of the con dence measure. We provide a simple application of con dence measures in which we ra...

Con dence measures have been found to be useful for a number tasks within the eld of Automatic Speech Recognition (ASR). For example, the use of con dence measures has been reported in the utterance veri cation, keyword spotting and Out-of-Vocabulary (OOV) word spotting literature. In this report, it is shown that so called 'hybrid Arti cial Neural Network/Hidden Markov Model' (HMM/ANN) systems...

This note presents three ways of constructing simultaneous condence intervals for linear estimates of linear functionals in inverse problems, including \Backus-Gilbert" estimates. Simultaneous con dence intervals are needed to compare estimates, for example, to nd spatial variations in a distributed parameter. The notion of simultaneous con dence intervals is introduced using coin tossing as an...

This article proposes an estimate of the odds ratio in a (2 £ 2) table obtained from studies in which the row totals are Ž xed by design, such as a phase II clinical trial. Our estimate,basedon themedianunbiasedestimateof the probabilitiesof success in the (2£2) table, will always be in the interval (0;1): Another estimate of the odds ratio which has such properties is obtained when adding .5 t...

A one-way randomeffectsmodel is consideredfor the log-transformedshift-longpersonal exposure measurements, where the random effect in the model represents an effect due to the worker. Following a previousapproach,we address a hypothesis-testingproblem involving the proportionof workers for whom the mean exposure exceeds the occupational exposure limit. A conŽ dence interval is constructed for t...

Automatic speech recognition (ASR) systems produce transcriptions for audio which sometimes contain errors. It is useful to know how much condence may be placed in this output being correct. Condence estimation is concerned with obtaining scores which quantify this level of condence. e development and application of a principled, žexible framework using conditional random eld (CRF) models f...

Constrained Maximum Likelihood (CML) is a new software module developed at Aptech Systems for the generation of maximum likelihood estimates of statistical models with general constraints on parameters. These constraints can be linear or nonlinear, equality or inequality. The software uses the Sequential Quadratic Programming method with various descent algorithms to iterate from a given starti...