Understanding temporally weakly supervised training: A case study for keyword spotting

The currently most prominent algorithm to train keyword spotting (KWS) models with deep neural networks (DNNs) requires strong supervision i.e., precise knowledge of the spoken keyword location in time. Thus, most KWS approaches treat the presence of redundant data, such as noise, within their training set as an obstacle. A common training paradigm to deal with data redundancies is to use temporally weakly supervised learning, which only requires providing labels on a coarse scale. This study explores the limits of DNN training using temporally weak labeling with applications in KWS. We train a simple end-to-end classifier on the common Google Speech Commands dataset with increased difficulty by randomly appending and adding noise to the training dataset. Our results indicate that temporally weak labeling can achieve comparable results to strongly supervised baselines while having a less stringent labeling requirement. In the presence of noise, weakly supervised models are capable to localize and extract target keywords without explicit supervision, leading to a performance increase compared to strongly supervised approaches

C1-continuous space-time discretization based on Hamilton's law of varying action

We develop a class of C1-continuous time integration methods that are applicable to conservative problems in elastodynamics. These methods are based on Hamilton's law of varying action. From the action of the continuous system we derive a spatially and temporally weak form of the governing equilibrium equations. This expression is first discretized in space, considering standard finite elements. The resulting system is then discretized in time, approximating the displacement by piecewise cubic Hermite shape functions. Within the time domain we thus achieve C1-continuity for the displacement field and C0-continuity for the velocity field. From the discrete virtual action we finally construct a class of one-step schemes. These methods are examined both analytically and numerically. Here, we study both linear and nonlinear systems as well as inherently continuous and discrete structures. In the numerical examples we focus on one-dimensional applications. The provided theory, however, is general and valid also for problems in 2D or 3D. We show that the most favorable candidate -- denoted as p2-scheme -- converges with order four. Thus, especially if high accuracy of the numerical solution is required, this scheme can be more efficient than methods of lower order. It further exhibits, for linear simple problems, properties similar to variational integrators, such as symplecticity. While it remains to be investigated whether symplecticity holds for arbitrary systems, all our numerical results show an excellent long-term energy behavior.Comment: slightly condensed the manuscript, added references, numerical results unchange

Simultaneous Bright- and Dark-Field X-ray Microscopy at X-ray Free Electron Lasers

The structures, strain fields, and defect distributions in solid materials underlie the mechanical and physical properties across numerous applications. Many modern microstructural microscopy tools characterize crystal grains, domains and defects required to map lattice distortions or deformation, but are limited to studies of the (near) surface. Generally speaking, such tools cannot probe the structural dynamics in a way that is representative of bulk behavior. Synchrotron X-ray diffraction based imaging has long mapped the deeply embedded structural elements, and with enhanced resolution, Dark Field X-ray Microscopy (DFXM) can now map those features with the requisite nm-resolution. However, these techniques still suffer from the required integration times due to limitations from the source and optics. This work extends DFXM to X-ray free electron lasers, showing how the $10^{12}$ photons per pulse available at these sources offer structural characterization down to 100 fs resolution (orders of magnitude faster than current synchrotron images). We introduce the XFEL DFXM setup with simultaneous bright field microscopy to probe density changes within the same volume. This work presents a comprehensive guide to the multi-modal ultrafast high-resolution X-ray microscope that we constructed and tested at two XFELs, and shows initial data demonstrating two timing strategies to study associated reversible or irreversible lattice dynamics

The Processing And Mental Representation Of Ing Variation

This dissertation examines the processing and mental representation of the sociolinguistic variable ING (thinking~thinkin\u27). Sociolinguists have asked questions about the locus of the ING variable using naturalistic speech data, which has resulted in a debate on whether the variable is phonological or morphological. These accounts of ING are not well-defined, and it is hard to isolate these representational properties in conversational data. I propose that locus of variation questions can be thought of as questions about the mental representation of variation, and that it would be fruitful to explore them using a highly-controllable tool from psycholinguistic research: primed lexical decision experiments. This tool is used to show that semantic, phonological, and morphological aspects of representation facilitate processing in different ways. I integrate sociolinguistic knowledge of variable ING with psycholinguistic knowledge on researching mental representations to ask: how are the socially meaningful variants -ing and -in\u27 mentally represented, and which aspects of shared representation contribute to how they are processed? Based on a framework of relevant aspects of representation, I establish a baseline understanding of the mental representation of -ing and -in\u27 across six experiments. Chapter 4 shows that -ing and -in\u27 prime both themselves and each other in words with unrelated stems (e.g. jumping-thinking), and uncovers an asymmetrical priming pattern between -ing and -in\u27 targets; -in\u27-in\u27 prime-target pairs enjoy a processing boost over -ing-ing, -in\u27-ing, and -ing-in\u27 pairs. Chapter 5 finds that this -in\u27 boost\u27 is temporally weak. Chapter 6 establishes that surface phonology does not contribute to the -in\u27 boost. Chapter 7 shows that the -in\u27 boost is insensitive to shared representation between prime-target stems. The results show robust and replicable affix priming for -ing and -in\u27. They also show a processing difference between the variants, and demonstrate properties of the -in\u27 boost. Taken together, the -in\u27 boost can be interpreted under a representation-based account, which suggests that -ing is the underlying phonological form, and that this can change to -in\u27 via application of a phonological rule. Finally, I propose future avenues of research that test this account and elaborate our understanding of the mental representation of variable ING

Bare and indefinite NPs in predicative position in French

This paper proposes a new analysis of the use of bare nouns vs. indefinite NPs in predicative position in French. We distinguish between predicational sentences (with the bare noun version) and equative sentences (with the indefinite version). We argue that bare nouns ascribe permanent properties to aspects of entities. As for the indefinites, we claim that they exhibit their specific reading and introduce an individual in a new situation, which is identified with the referent of the subject

Electrophysiological correlates of event segmentation: how does the human mind process ongoing activity?

The human mind decodes, processes, and makes sense of a continual flow of dynamic information, taken from an array of sensory inputs. Compelling behavioural and neuroimaging evidence reveals that humans segment activities into meaningful chunks for processing, and this phenomenon has profound implications for learning, memory and understanding the world around us (Newtson, 1973; Zacks and Tversky, 2001; Zacks et al., 2001). Whilst the existence of event segmentation is widely accepted, it remains unclear what cognitive mechanisms drive this ability.This thesis constitutes a series of behavioural and neuroimaging experiments that investigate top-down and bottom-up influences on event segmentation. The neuroimaging studies presented here are novel; they extend the field by investigating event segmentation using scalp-recorded electroencephalography (EEG). Event Related Potentials (ERPs, derived from EEG using signal-averaging procedures) showed that the perceptual processing of event boundaries is differentially sensitive to the segmentation of activities into small or large chunks, consistent with findings from previous neuroimaging research (Zacks et al., 2001). In contrast with previous findings, the electrophysiological investigations elicited responses that were clearly affected by manipulating top-down information (e.g., participant's knowledge about the activity being segmented). The results from the studies reported in the thesis support an account of the perceptual processing of event boundaries, which incorporates both top-down and bottom-up influences

Spatial management of groundfish resources in the Gulf of Maine and Georges Bank

In the marine environment, studies suggest that overfishing suppresses sustainability and resilience in fish populations. In the 1990s, the National Marine Fisheries Service (NMFS) implemented five large year-round fishery closures in the Gulf of Maine and Georges Bank. These closures are partially protected marine protected areas (MPAs) restricting commercial fishing with bottom-tending gears. To date, evaluation of their performance has focused on the productivity of individual species. This research aims to understand if fish biodiversity changed after implementation of the five large fisheries closures. Here, a variety of datasets and statistical approaches are used. Modern patterns constructed from NMFS bottom-trawl surveys (1971--2005) demonstrated that fish species richness increased in some areas, as species evenness declined. Fish species composition changed from demersal species to more abundant pelagic species inside and outside of the fisheries closures. Likely drivers of these changes included destruction of habitat by over fishing, and climate and fishery driven disturbance. After constructing a historical baseline for the Western Gulf of Maine and Georges Bank, total genera detected by historical Fishhawk research trawl surveys in the late 19th century were 2 times greater than the number appearing in NMFS bottom-trawl surveys (1963-2007); however, in contrast, NMFS bottom-trawl surveys detected more fish genera. Guild composition was similar for both surveys with respect to demersal, but not pelagic species. These differences were explained by changes in survey sampling technology, fishing pressure, and ecosystem resilience. Recent seasonal patterns of fish species richness from multiple fisheries-independent and dependent datasets showed that inshore areas (such as Massachusetts and Ipswich Bays), the transition between the Gulf of Maine and Georges Bank, and eastern Georges Bank exhibited high fish species richness. When data was available from observed commercial otter-trawl tows adjacent to or within closures, high richness areas occurred, regardless of season. Likely processes influencing species richness over the region and near the fishery closures consisted of seasonal prey availability, oceanographic conditions, and fishing pressure. High effort around fishery closure boundaries had important implications for the effective design of MPAs and future management of groundfish