Optimizing expected word error rate via sampling for speech recognition

State-level minimum Bayes risk (sMBR) training has become the de facto standard for sequence-level training of speech recognition acoustic models. It has an elegant formulation using the expectation semiring, and gives large improvements in word error rate (WER) over models trained solely using cross-entropy (CE) or connectionist temporal classification (CTC). sMBR training optimizes the expected number of frames at which the reference and hypothesized acoustic states differ. It may be preferable to optimize the expected WER, but WER does not interact well with the expectation semiring, and previous approaches based on computing expected WER exactly involve expanding the lattices used during training. In this paper we show how to perform optimization of the expected WER by sampling paths from the lattices used during conventional sMBR training. The gradient of the expected WER is itself an expectation, and so may be approximated using Monte Carlo sampling. We show experimentally that optimizing WER during acoustic model training gives 5% relative improvement in WER over a well-tuned sMBR baseline on a 2-channel query recognition task (Google Home)

How Did You Study For the Test? Measuring the Impact of an Online Study Skills Module

The rationale for this project is rooted in the importance of students engaging in effective study habits in preparation for exams at the collegiate level. Many investigations into study habits rely on student self reporting. In this project we use online student activity data to supplement survey responses and attempt to determine whether an online study skills module a) impacted exam performance and b) changed student study habits. Students in online and blended courses were provided with an online study skills module that recommended effective study strategies. We examined clickstream data to identify the students who accessed the study skills module and then compared exam scores between those students who accessed the module and those that did not. Students were also asked to complete an anonymous survey to ask about their studying practices, including their experience with the study skills module. Findings suggest that the availability of an online study resource did not affect student study habits or exam grades

Adaptive Floor Hockey Device

Sean is a young boy living with ataxic cerebral palsy. Ataxic cerebral palsy affects Sean’s balance and coordination, so he uses a walker to increase his mobility. Sean would like to play Special Olympics Floor Hockey but his walker prevents him from participating. The goal of this Senior project was to develop a device to be attached to his previous walker to allow Sean to play floor hockey in the least restrictive environment possible. The Adaptive Floor Hockey Device is the product we designed to satisfy this need

A Cross Sectional Study of Mostly African- American Men Examining Mental Health and Child Behavior

Background: Home visiting receives bipartisan support at both the state and federal level, because several models have demonstrated significant results in both reduction of child maltreatment as well as parenting behavior modification. Yet, parenting research and services lack further engagement and involvement as a primary component. That is, even though research has shown that fathers play an integral role in child development, there is very little research done in which fathers are the primary focus; most of this research focuses on mothers. When it comes to serving children who are victims of child abuse and neglect, this is a problem at both the programmatic and legislative level. Methods: This study took place within the context of a broader NIH funded trial to examine the efficacy of an adapted (technologically enhanced) version of an evidence-based parenting program, SafeCare, for fathers. This was a cross-sectional examination of the results from a survey in which mostly African-American, at-risk fathers (n=84), reported on – using putative measures – parenting practices, mental health, and behavior of their children. This initial assessment used linear regression to examine the association between fathers’ mental health and their child’s externalizing and internalizing problem behaviors. Results: On average, higher levels of father depression and anxiety corresponded to higher scores for child behavior problems. That is, there was a significant correlation between the fathers’ anxiety and depression and the child’s problem behaviors. Conclusions: These findings suggest a need for acknowledging the father’s role in child development as well as any potential external factors that might have a pernicious effect on the father’s mental state[s]. In addition, more attention should be given to separating data within studies that examine both mothers and fathers in order to assess individual effects by each parent

A formulation of the autoregressive HMM for speech synthesis

We present a formulation of the autoregressive HMM for speech synthesis and compare it to the standard HMM synthesis framework and the trajectory HMM. We give details of how to do efficient parameter estimation and synthesis with the autoregressive HMM and discuss consequences of the autoregressive HMM model. There are substantial similarities between the three models, which we explore. The advantages of the autoregressive HMM are that it uses the same model for parameter estimation and synthesis in a consistent way, in contrast to the standard HMM synthesis framework, and that it supports easy and efficient parameter estimation, in contrast to the trajectory HMM.This research was funded by the European Community's Seventh Framework Programme (FP7/2007-2013), grant agreement 213845 (EMIME)

Fast, low-artifact speech synthesis considering global variance

Copyright 2013 IEEE.Speech parameter generation considering global variance (GV generation) is widely acknowledged to dramatically improve the quality of synthetic speech generated by HMM-based systems. However it is slower and has higher latency than the standard speech parameter generation algorithm. In addition it is known to produce artifacts, though existing approaches to prevent artifacts are effective. We present a simple new theoretical analysis of speech parameter generation considering global variance based on Lagrange multipliers. This analysis sheds light on one source of artifacts and suggests a way to reduce their occurrence. It also suggests an approximation to exact GV generation that allows fast, low latency synthesis. In a subjective evaluation our fast approximation shows no degradation in naturalness compared to conventional GV generation.This work was supported in part by EPSRC Programme Grant EP/I031022/1 (Natural Speech Technology)

The effect of using normalized models in statistical speech synthesis

The standard approach to HMM-based speech synthesis is inconsistent in the enforcement of the deterministic constraints between static and dynamic features. The trajectory HMM and autoregressive HMM have been proposed as normalized models which rectify this inconsistency. This paper investigates the practical effects of using these normalized models, and examines the strengths and weaknesses of the different models as probabilistic models of speech. The most striking difference observed is that the standard approach greatly underestimates predictive variance. We argue that the normalized models have better predictive distributions than the standard approach, but that all the models we consider are still far from satisfactory probabilistic models of speech. We also present evidence that better intra-frame correlation modelling goes some way towards improving existing normalized models.This work was partly supported by the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement 213845 (EMIME)

Investigating the Moral Challenges Experienced by UK Service Police Veterans

Previous research has explored the negative effects of exposure to potentially morally injurious events among armed forces veterans and active-duty military personnel generally. However, this current pilot research provides a unique contribution to the extant research literature by examining the specific moral challenges experienced by a potentially at-risk and under-researched sub-group of military personnel. Semi-structured interviews were conducted with 10 United Kingdom (UK) Service Police veterans to identify any moral challenges encountered during their military service and to investigate the experience of moral dissonance underlying these events. Using Interpretative Phenomenological Analysis (IPA), four main themes (with sub-themes) emerged from the data: (a) violation of a moral code, (b) experience of disillusionment, (c) attempted resolution of moral dissonance, and (d) risk and protective factors for moral dissonance. Evidence of the types of moral challenges encountered by Service Police veterans during their military service and the negative consequences of moral dissonance was explored for the first time. Some of these findings overlap with existing evidence from non-Service Police research, although novel insights were also identified, such as the attempts of Service Police veterans to resolve moral dissonance through acting with moral courage, self-preservation, or seeking acceptance. The current research therefore provides a rationale for further investigation into the experience of moral dissonance and impact of exposure to morally injurious events in this sub-population of veterans. Potential implications for advancing conceptual understanding of moral injury and informing interventions to prevent the development of morally injurious outcomes are discussed

BCO-DMO Quick Guide

BCO-DMO, a repository funded by the National Science Foundation (NSF), supports the oceanographic research community’s data needs throughout the entire data life cycle. This guide describes the services available from BCO-DMO from proposal to preservation and highlights phases where researchers engage significantly with the office.Curating and providing open access to research data is a collaborative process. This process may be thought of as a life cycle with data passing through various phases. Each phase has its own associated actors, roles, and critical activities. Good data management practices are necessary for all phases, from proposal to preservation.NSF #143557

The Economic Consequences of the East Palestine Train Derailment

The Center for Economic Development at Cleveland State University, in partnership with the Upjohn Institute for Employment Research, is engaged in an ongoing effort to track the economic consequences of the Norfolk Southern train derailment in East Palestine, Ohio, on the evening of February 3, 2023. This initial report focuses strictly on effects felt throughout the city of East Palestine, with special attention paid to the evacuation area, and covers the period from the date of the derailment until two weeks afterward (through February 17, 2023). This period coincides with the mandatory evacuation time ordered by the office of Governor Mike DeWine and serves to frame the early economic impacts on the community. The results will show conservative estimations and act as a starting point for understanding the extent of the economic impact of the derailment on the people of East Palestine. This will be the first in a series of reports examining the immediate economic impact of the train derailment and mitigation of derailment consequences using public and private assistance. This report aims to bring attention to the magnitude of economic losses suffered by the community and the response needed from the government, first responders, and the company to compensate for those damages and provide the appropriate remediation services