Improving LVCSR system combination using neural network language model cross adaptation

State-of-the-art large vocabulary continuous speech recognition (LVCSR) systems often combine outputs from multiple subsystems developed at different sites. Cross system adaptation can be used as an alternative to direct hypothesis level combination schemes such as ROVER. The standard approach involves only cross adapting acoustic models. To fully exploit the complimentary features among sub-systems, language model (LM) cross adaptation techniques can be used. Previous research on multi-level n-gram LM cross adaptation is extended to further include the cross adaptation of neural network LMs in this paper. Using this improved LM cross adaptation framework, significant error rate gains of 4.0%-7.1% relative were obtained over acoustic model only cross adaptation when combining a range of Chinese LVCSR sub-systems used in the 2010 and 2011 DARPA GALE evaluations. Copyright © 2011 ISCA.

Use of contexts in language model interpolation and adaptation

Language models (LMs) are often constructed by building multiple individual component models that are combined using context independent interpolation weights. By tuning these weights, using either perplexity or discriminative approaches, it is possible to adapt LMs to a particular task. This paper investigates the use of context dependent weighting in both interpolation and test-time adaptation of language models. Depending on the previous word contexts, a discrete history weighting function is used to adjust the contribution from each component model. As this dramatically increases the number of parameters to estimate, robust weight estimation schemes are required. Several approaches are described in this paper. The first approach is based on MAP estimation where interpolation weights of lower order contexts are used as smoothing priors. The second approach uses training data to ensure robust estimation of LM interpolation weights. This can also serve as a smoothing prior for MAP adaptation. A normalized perplexity metric is proposed to handle the bias of the standard perplexity criterion to corpus size. A range of schemes to combine weight information obtained from training data and test data hypotheses are also proposed to improve robustness during context dependent LM adaptation. In addition, a minimum Bayes' risk (MBR) based discriminative training scheme is also proposed. An efficient weighted finite state transducer (WFST) decoding algorithm for context dependent interpolation is also presented. The proposed technique was evaluated using a state-of-the-art Mandarin Chinese broadcast speech transcription task. Character error rate (CER) reductions up to 7.3 relative were obtained as well as consistent perplexity improvements. © 2012 Elsevier Ltd. All rights reserved.

Generalization in Adaptation to Stable and Unstable Dynamics

Humans skillfully manipulate objects and tools despite the inherent instability. In order to succeed at these tasks, the sensorimotor control system must build an internal representation of both the force and mechanical impedance. As it is not practical to either learn or store motor commands for every possible future action, the sensorimotor control system generalizes a control strategy for a range of movements based on learning performed over a set of movements. Here, we introduce a computational model for this learning and generalization, which specifies how to learn feedforward muscle activity in a function of the state space. Specifically, by incorporating co-activation as a function of error into the feedback command, we are able to derive an algorithm from a gradient descent minimization of motion error and effort, subject to maintaining a stability margin. This algorithm can be used to learn to coordinate any of a variety of motor primitives such as force fields, muscle synergies, physical models or artificial neural networks. This model for human learning and generalization is able to adapt to both stable and unstable dynamics, and provides a controller for generating efficient adaptive motor behavior in robots. Simulation results exhibit predictions consistent with all experiments on learning of novel dynamics requiring adaptation of force and impedance, and enable us to re-examine some of the previous interpretations of experiments on generalization. © 2012 Kadiallah et al.

Language model cross adaptation for LVCSR system combination

State-of-the-art large vocabulary continuous speech recognition (LVCSR) systems often combine outputs from multiple sub-systems that may even be developed at different sites. Cross system adaptation, in which model adaptation is performed using the outputs from another sub-system, can be used as an alternative to hypothesis level combination schemes such as ROVER. Normally cross adaptation is only performed on the acoustic models. However, there are many other levels in LVCSR systems' modelling hierarchy where complimentary features may be exploited, for example, the sub-word and the word level, to further improve cross adaptation based system combination. It is thus interesting to also cross adapt language models (LMs) to capture these additional useful features. In this paper cross adaptation is applied to three forms of language models, a multi-level LM that models both syllable and word sequences, a word level neural network LM, and the linear combination of the two. Significant error rate reductions of 4.0-7.1% relative were obtained over ROVER and acoustic model only cross adaptation when combining a range of Chinese LVCSR sub-systems used in the 2010 and 2011 DARPA GALE evaluations. © 2012 Elsevier Ltd. All rights reserved.

Kernelized log linear models for continuous speech recognition

Large margin criteria and discriminative models are two effective improvements for HMM-based speech recognition. This paper proposed a large margin trained log linear model with kernels for CSR. To avoid explicitly computing in the high dimensional feature space and to achieve the nonlinear decision boundaries, a kernel based training and decoding framework is proposed in this work. To make the system robust to noise a kernel adaptation scheme is also presented. Previous work in this area is extended in two directions. First, most kernels for CSR focus on measuring the similarity between two observation sequences. The proposed joint kernels defined a similarity between two observation-label sequence pairs on the sentence level. Second, this paper addresses how to efficiently employ kernels in large margin training and decoding with lattices. To the best of our knowledge, this is the first attempt at using large margin kernel-based log linear models for CSR. The model is evaluated on a noise corrupted continuous digit task: AURORA 2.0. © 2013 IEEE.

Exploiting the Transients of Adaptation for RoQ Attacks on Internet Resources

In this paper, we expose an unorthodox adversarial attack that exploits the transients of a system's adaptive behavior, as opposed to its limited steady-state capacity. We show that a well orchestrated attack could introduce significant inefficiencies that could potentially deprive a network element from much of its capacity, or significantly reduce its service quality, while evading detection by consuming an unsuspicious, small fraction of that element's hijacked capacity. This type of attack stands in sharp contrast to traditional brute-force, sustained high-rate DoS attacks, as well as recently proposed attacks that exploit specific protocol settings such as TCP timeouts. We exemplify what we term as Reduction of Quality (RoQ) attacks by exposing the vulnerabilities of common adaptation mechanisms. We develop control-theoretic models and associated metrics to quantify these vulnerabilities. We present numerical and simulation results, which we validate with observations from real Internet experiments. Our findings motivate the need for the development of adaptation mechanisms that are resilient to these new forms of attacks.

Adaptation of Dopamine Neurons' Mismatch Sensitivity Is not Compatible With Reinforcement Learning Theory

Recent electrophysical data inspired the claim that dopaminergic neurons adapt their mismatch sensitivities to reflect variances of expected rewards. This contradicts reward prediction error theory and most basal ganglia models. Application of learning principles points to a testable alternative interpretation-of the same data-that is compatible with existing theory.

Redox remodelling in diaphragm muscle adaptation to chronic sustained hypoxia

Chronic sustained hypoxia (CH) induces functional weakness, atrophy, and mitochondrial remodelling in the diaphragm muscle. Animal models of CH present with changes similar to patients with respiratory-related disease, thus, elucidating the molecular mechanisms driving these adaptations is clinically important. We hypothesize that ROS are pivotal in diaphragm muscle adaptation to CH. C57BL6/J mice were exposed to CH (FiO2=0.1) for one, three, and six weeks. Sternohyoid (upper airway dilator), extensor digitorum longus (EDL), and soleus were studied as reference muscles as well as the diaphragm. The diaphragm was profiled using a redox proteomics approach followed by mass spectrometry. Following this, redox-modified metabolic enzyme activities and atrophy signalling were assessed using spectrophotometric assays and ELISA. Diaphragm isotonic performance was assessed after six weeks of CH ± chronic antioxidant supplementation. Protein carbonyl and free thiol content in the diaphragm were increased and decreased respectively after six weeks of CH – indicative of protein oxidation. These changes were temporally modulated and muscle specific. Extensive remodelling of metabolic proteins occurred and the stress reached the cross-bridge. Metabolic enzyme activities in the diaphragm were, for the most part, decreased by CH and differential muscle responses were observed. Redox sensitive chymotrypsin-like proteasome activity of the diaphragm was increased and atrophy signalling was observed through decreased phospho-FOXO3a and phospho-mTOR. Phospho-p38 MAPK content was increased and this was attenuated by antioxidant treatment. Hypoxia decreased power generating capacity of the diaphragm and this was restored by N-acetyl-cysteine (NAC) but not by tempol. Redox remodelling is pivotal for diaphragm adaptation to chronic sustained hypoxia. Muscle changes are dependent on duration of the hypoxia stimulus, activity profile of the muscle, and molecular composition of the muscle. The working respiratory muscles and slow oxidative fibres are particularly susceptible. NAC (antioxidant) may be useful as an adjunct therapy in respiratory-related diseases characterised by hypoxic stress.

Climate change, water resources, and the politics of adaptation in the Middle East and North Africa

Through an examination of global climate change models combined with hydrological data on deteriorating water quality in the Middle East and North Africa (MENA), we elucidate the ways in which the MENA countries are vulnerable to climate-induced impacts on water resources. Adaptive governance strategies, however, remain a low priority for political leaderships in the MENA region. To date, most MENA governments have concentrated the bulk of their resources on large-scale supply side projects such as desalination, dam construction, inter-basin water transfers, tapping fossil groundwater aquifers, and importing virtual water. Because managing water demand, improving the efficiency of water use, and promoting conservation will be key ingredients in responding to climate-induced impacts on the water sector, we analyze the political, economic, and institutional drivers that have shaped governance responses. While the scholarly literature emphasizes the importance of social capital to adaptive governance, we find that many political leaders and water experts in the MENA rarely engage societal actors in considering water risks. We conclude that the key capacities for adaptive governance to water scarcity in MENA are underdeveloped. © 2010 Springer Science+Business Media B.V.

Enhancing the usability of numerical models with case-based reasoning

Numerical models are important tools used in engineering fields to predict the behaviour and the impact of physical elements. There may be advantages to be gained by combining Case-Based Reasoning (CBR) techniques with numerical models. This paper considers how CBR can be used as a flexible query engine to improve the usability of numerical models. Particularly they can help to solve inverse and mixed problems, and to solve constraint problems. We discuss this idea with reference to the illustrative example of a pneumatic conveyor problem. The paper describes example problems faced by design engineers in this context and the issues that need to be considered in this approach. Solution of these problems require methods to handle constraints in both the retrieval phase and the adaptation phase of a typical CBR cycle. We show approaches to the solution of these problesm via a CBR tool.

The introduction of social adaptation within evacuation modelling

In recent history, a number of tragic events have borne a consistent message; the social structures that existed prior to and during the evacuation significantly affected the decisions made and the actions adopted by the evacuating population in response to the emergency. This type of influence over behaviour has long been neglected in the modelling community. This paper is an attempt to introduce some of these considerations into evacuation models and to demonstrate their impact. To represent this type of behaviour within evacuation models a mechanism to represent the membership and position within social hierarchies is established. In addition, individuals within the social groupings are given the capacity to communicate relevant pieces of data such as the need to evacuate—impacting the response time—and the location of viable exits—impacting route selection. Furthermore, the perception and response to this information is also affected by the social circumstances in which individuals find themselves. Copyright © 2005 John Wiley & Sons, Ltd.

The direction aftereffect is driven by adaptation of local motion detectors

The processing of motion information by the visual system can be decomposed into two general stages; point-by-point local motion extraction, followed by global motion extraction through the pooling of the local motion signals. The direction aftereVect (DAE) is a well known phenomenon in which prior adaptation to a unidirectional moving pattern results in an exaggerated perceived direction diVerence between the adapted direction and a subsequently viewed stimulus moving in a diVerent direction. The experiments in this paper sought to identify where the adaptation underlying the DAE occurs within the motion processing hierarchy. We found that the DAE exhibits interocular transfer, thus demonstrating that the underlying adapted neural mechanisms are binocularly driven and must, therefore, reside in the visual cortex. The remaining experiments measured the speed tuning of the DAE, and used the derived function to test a number of local and global models of the phenomenon. Our data provide compelling evidence that the DAE is driven by the adaptation of motion-sensitive neurons at the local-processing stage of motion encoding. This is in contrast to earlier research showing that direction repulsion, which can be viewed as a simultaneous presentation counterpart to the DAE, is a global motion process. This leads us to conclude that the DAE and direction repulsion reflect interactions between motion-sensitive neural mechanisms at different levels of the motion-processing hierarchy.

Climate Change Adaptation for Conservation in Madagascar

Madagascar's imperilled biota are now experiencing the effects of a new threat—climate change (Raxworthy et al. 2008). With more than 90% endemism among plants, mammals, reptiles and amphibians, the stakes are high. The pristine landscapes that allowed this exceptional biodiversity to survive past climate changes are largely gone. Deforestation has claimed approximately 90% of the island's natural forest (Ingram & Dawson 2005; Harper et al. 2007) and what remains is highly fragmented, providing a poor template for large-scale species range shifts. The impacts of current and future climate change may therefore be much different than past impacts, with profound implications for biodiversity.
We review evidence of past response to climate change, models of future change and projected biological response, developing insights to formulate adaptation actions for reducing extinction in Madagascar's biota. We then explore the cost of implementing actions and examine new income opportunities developing through efforts to mitigate climate change.

Adaptation and Reintegration of Proprioceptive Information in Young and Older Adults' Postural Control

We investigated age-related changes in adaptation and sensory reintegration in postural control without vision. In two sessions, participants adapted their posture to sway reference and to reverse sway reference conditions, the former reducing (near eliminating) and the latter enhancing (near doubling) proprioceptive information for posture by means of support-surface rotations in proportion to body sway. Participants stood on a stable platform for 3 min (baseline) followed by 18 min of sway reference or reverse sway reference (adaptation) and finally again on a stable platform for 3 min (reintegration). Results showed that when inaccurate proprioception was introduced, anterior-posterior (AP) sway path length increased in comparable levels in the two age groups. During adaptation, young and older adults reduced postural sway at the same rate. On restoration of the stable platform in the reintegration phase, a sizeable aftereffect of increased AP path length was observed in both groups, which was greater in magnitude and duration for older adults. In line with linear feedback models of postural control, spectral analyses showed that this aftereffect differed between the two platform conditions. In the sway-referenced condition, a switch from low- to high-frequency COP sway marked the transition from reduced to normal proprioceptive information. The opposite switch was observed in the reverse sway referenced condition. Our findings illustrate age-related slowing in participants' postural control adjustments to sudden changes in environmental conditions. Over and above differences in postural control, our results implicate sensory reweighting as a specific mechanism highly sensitive to age-related decline.

Climate Adaptation: The future of extra-care housing for the elderly in the United Kingdom.

This paper describes the result of a project to develop climate adaptation design strategies funded by the UK’s Technology Strategy Board. The aim of the project was to look at the effects of climate change in the distant future (2080) on a vulnerable group such as older people with special needs and see how architectural design strategies and technologies may be used today to help mitigate problems ahead caused by climate change.
Older people are the most vulnerable sector of society and are particularly at risk in extreme weather, either excess cold in winter or continual high temperatures in summer. In the UK it is predicted that average temperatures may rise by as much as 8 degrees in Summer by 2080 and there will be a 20% greater chance of extreme weather events. This will place extreme stress on the building stock which is designed for today’s mild maritime climate.
The project took a current proposal for an extra-care home for the elderly designed to 2010 regulations and developed a road map to 2080 using climate models developed by the UK Meteorological Office. This allowed the current design to be assessed using future climatic data, proposals for improvement of the scheme to be made within existing constraints and also a new scheme to be developed from first principals using this data, and projections of new technologies that will be available. By comparing these schemes, the approach allowed a reassessment of the initial scheme, and allowed a new design to be developed that offered a more flexible solution incorporating future retrofit which allows new renewable technologies for heating, cooling and water storage to be added at a later date.