This paper reports results on an experiment to use corrective training techniques for rapid acoustic speaker adaptation in a semi-continuous speech recognition system. Decoder output is used to adjust HMM acoustic models to improve discrimination between correct words and near misses. Twenty sentences are used as an adaptation set. A speech recognizer is run on each utterance to generate a word...

.....................................................................................xii CHAPTER ONE: INTRODUCTION....................................................... 1 The Problem in Perspective.............................................................3 Corrective Feedback............................................................4 Barriers to accepting corrective feedback received........

Background: Work-related musculoskeletal disorders are major causes of absenteeism, increased costs, and human injuries among computer users. This study aimed to examine the effects of ergonomics training and corrective exercises on musculoskeletal disorders among a gas company computer users. Material and Methods: This experimental study was conducted on 19 office computer users who participa...

This paper focuses on an error-corrective method through reranking of hypotheses in speech recognition. Some recent work investigated corrective models that can be used to rescore hypotheses so that a hypothesis with a smaller error rate has a higher score. Discriminative training such as perceptron algorithm can be used to estimate such corrective models. In discriminative training, how to cho...

Although there is variability in nonnative grammar learning outcomes, the contributions of training paradigm design and memory subsystems are not well understood. To examine this, we presented learners with an artificial grammar that formed words via simple and complex morphophonological rules. Across three experiments, we manipulated training paradigm design and measured subjects' declarative,...

This paper proposed a maximum model distance (MMD) approach for HMM-based speech recognition. MMD uses the whole training set to estimate the parameters of each HMM while the traditional maximum likelihood (ML) uses only those data labeled for the model. Theoretical and practical issues concerning this approach in speech recognition are investigated. Both speakerdependent and multi-speaker expe...

We evaluate a simple extension of the corrective training algorithm for reestimation of the acoustic parameters, using | in addition to misrecognized sentences | also a selection of correctly recognized sentences for discrimination. Our approach (called \rival training") is implementationally much less expensive than lattice{based discriminative training methods, since we apply a \hard" thresho...