Phone-level pronunciation scoring and assessment for interactive language learning

This paper investigates a method of automatic pronunciation scoring for use in computer-assisted language learning (CALL) systems. The method utilizes a likelihood-based `Goodness of Pronunciation' (GOP) measure which is extended to include individual thresholds for each phone based on both averaged native confidence scores and on rejection statistics provided by human judges. Further improvements are obtained by incorporating models of the subject's native language and by augmenting the recognition networks to include expected pronunciation errors. The various GOP measures are assessed using a specially recorded database of non-native speakers which has been annotated to mark phone-level pronunciation errors. Since pronunciation assessment is highly subjective, a set of four performance measures has been designed, each of them measuring different aspects of how well computer-derived phone-level scores agree with human scores. These performance measures are used to cross-validate the reference annotations and to assess the basic GOP algorithm and its refinements. The experimental results suggest that a likelihood-based pronunciation scoring metric can achieve usable performance, especially after applying the various enhancements.

KLAIR: A virtual infant for spoken language acquisition research

Recent research into the acquisition of spoken language has stressed the importance of learning through embodied linguistic interaction with caregivers rather than through passive observation. However the necessity of interaction makes experimental work into the simulation of infant speech acquisition difficult because of the technical complexity of building real-time embodied systems. In this paper we present KLAIR: a software toolkit for building simulations of spoken language acquisition through interactions with a virtual infant. The main part of KLAIR is a sensori-motor server that supplies a client machine learning application with a virtual infant on screen that can see, hear and speak. By encapsulating the real-time complexities of audio and video processing within a server that will run on a modern PC, we hope that KLAIR will encourage and facilitate more experimental research into spoken language acquisition through interaction. Copyright © 2009 ISCA.

RNAi, DRD1, and histone methylation actively target developmentally important Non-CG DNA methylation in Arabidopsis

Cytosine DNA methylation protects eukaryotic genomes by silencing transposons and harmful DNAs, but also regulates gene expression during normal development. Loss of CG methylation in the Arabidopsis thaliana met1 and ddm1 mutants causes varied and stochastic developmental defects that are often inherited independently of the original met1 or ddm1 mutation. Loss of non-CG methylation in plants with combined mutations in the DRM and CMT3 genes also causes a suite of developmental defects. We show here that the pleiotropic developmental defects of drm1 drm2 cmt3 triple mutant plants are fully recessive, and unlike phenotypes caused by met1 and ddm1, are not inherited independently of the drm and cmt3 mutations. Developmental phenotypes are also reversed when drm1 drm2 cmt3 plants are transformed with DRM2 or CMT3, implying that non-CG DNA methylation is efficiently re-established by sequence-specific signals. We provide evidence that these signals include RNA silencing though the 24-nucleotide short interfering RNA (siRNA) pathway as well as histone H3K9 methylation, both of which converge on the putative chromatin-remodeling protein DRD1. These signals act in at least three partially intersecting pathways that control the locus-specific patterning of non-CG methylation by the DRM2 and CMT3 methyltransferases. Our results suggest that non-CG DNA methylation that is inherited via a network of persistent targeting signals has been co-opted to regulate developmentally important genes. © 2006 Chan et al.

How to avoid the problems of target-setting

Purpose: Advocates and critics of target-setting in the workplace seem unable to reach beyond their own well-entrenched battle lines. While the advocates of goal-directed behaviour point to what they see as demonstrable advantages, the critics of target-setting highlight equally demonstrable disadvantages. Indeed, the academic literature on this topic is currently mired in controversy, with neither side seemingly capable of envisaging a better way forward. This paper seeks to break the current deadlock and move thinking forward in this important aspect of performance measurement and management by outlining a new, more fruitful approach, based on both theory and practical experience. Design/methodology/approach: The topic was approached in three phases: assembling and reading key academic and other literature on the subject of target-setting and goal-directed behaviour, with a view to understanding, in depth, the arguments advanced by the advocates and critics of target-setting; comparing these published arguments with one's own experiential findings, in order to bring the essence of disagreement into much sharper focus; and then bringing to bear the academic and practical experience to identify the essential elements of a new, more fruitful approach offering all the benefits of goal-directed behaviour with none of the typical disadvantages of target-setting. Findings: The research led to three key findings: the advocates of goal-directed behaviour and critics of target-setting each make valid points, as seen from their own current perspectives; the likelihood of these two communities, left to themselves, ever reaching a new synthesis, seems vanishingly small (with leading thinkers in the goal-directed behaviour community already acknowledging this); and, between the three authors, it was discovered that their unusual combination of academic study and practical experience enabled them to see things differently. Hence, they would like to share their new thinking more widely. Research limitations/implications: The authors fully accept that their paper is informed by extensive practical experience and, as yet, there have been no opportunities to test their findings, conclusions and recommendations through rigorous academic research. However, they hope that the paper will move thinking forward in this arena, thereby informing future academic research. Practical implications: The authors hope that the practical implications of the paper will be significant, as it outlines a novel way for organisations to capture the benefits of goal-directed behaviour with none of the disadvantages typically associated with target-setting. Social implications: Given that increased efficiency and effectiveness in the management of organisations would be good for society, the authors think the paper has interesting social implications. Originality/value: Leading thinkers in the field of goal-directed behaviour, such as Locke and Latham, and leading critics of target-setting, such as Ordóñez et al. continue to argue with one another - much like, at the turn of the nineteenth century, proponents of the "wave theory of light" and proponents of the "particle theory of light" were similarly at loggerheads. Just as this furious scientific debate was ultimately resolved by Taylor's experiment, showing that light could behave both as a particle and wave at the same time, the authors believe that the paper demonstrates that goal-directed behaviour and target-setting can successfully co-exist. © Emerald Group Publishing Limited.

Developing a technology intelligence strategy at kodak european research: Scan & target

OVERVIEW: Kodak European Research (KER) developed a strategy for technology intelligence based on a theoretical model developed by Kerr et al. (2006). KER scouts designed and implemented a four-step approach to identify relevant technologies and research centers across Europe, Africa and the Middle East. The approach provides clear guidance for integrating web searches, scouting trips, networking and interactions with intermediaries. KER's example illustrates how companies can organize themselves to look outside corporate boundaries in search of technologies relevant for their business. The approach may be useful to those in other companies who have been asked to start a technology intelligence activity. © 2010 Industrial Research Institute, Inc.

Statistical parametric speech synthesis based on speaker and language factorization

An increasingly common scenario in building speech synthesis and recognition systems is training on inhomogeneous data. This paper proposes a new framework for estimating hidden Markov models on data containing both multiple speakers and multiple languages. The proposed framework, speaker and language factorization, attempts to factorize speaker-/language-specific characteristics in the data and then model them using separate transforms. Language-specific factors in the data are represented by transforms based on cluster mean interpolation with cluster-dependent decision trees. Acoustic variations caused by speaker characteristics are handled by transforms based on constrained maximum-likelihood linear regression. Experimental results on statistical parametric speech synthesis show that the proposed framework enables data from multiple speakers in different languages to be used to: train a synthesis system; synthesize speech in a language using speaker characteristics estimated in a different language; and adapt to a new language. © 2012 IEEE.