Improving Robustness of Neural Inverse Text Normalization via Data-Augmentation, Semi-Supervised Learning, and Post-Aligning Method

Inverse text normalization (ITN) is crucial for converting spoken-form into written-form, especially in the context of automatic speech recognition (ASR). While most downstream tasks of ASR rely on written-form, ASR systems often output spoken-form, highlighting the necessity for robust ITN in product-level ASR-based applications. Although neural ITN methods have shown promise, they still encounter performance challenges, particularly when dealing with ASR-generated spoken text. These challenges arise from the out-of-domain problem between training data and ASR-generated text. To address this, we propose a direct training approach that utilizes ASR-generated written or spoken text, with pairs augmented through ASR linguistic context emulation and a semi-supervised learning method enhanced by a large language model, respectively. Additionally, we introduce a post-aligning method to manage unpredictable errors, thereby enhancing the reliability of ITN. Our experiments show that our proposed methods remarkably improved ITN performance in various ASR scenarios.Comment: submitted to ICASSP 202

Understanding Rheology and Microstructure of Thermoresponsive Nanoemulsions as a Model System of Colloidal Suspensions

Nanoemulsions – nanoscale droplet suspensions – in polymeric solution have been widely used in many fields from consumer products to advanced technology. Due to their nanoscopic dimensions, they exhibit unique physical behavior in terms of their rheology and microstructure, both at rest and under flow. However, mechanisms that give rise the interesting phenomena observed in nanodroplet-polymer mixtures are poorly understood. Thus, the goals of this thesis are to develop a model nanoemulsion-polymer system to impart control over polymer-droplet and droplet-droplet interactions, use it to investigate the mechanisms colloidal behavior of nanodroplets in polymeric solutions, and to determine how these behaviors influence suspension microstructure, dynamics and rheology. For these purposes, we choose to study thermoresponsive oil-in-water nanoemulsions as a model system. The systems include polydimethylsiloxane (PDMS) oil nanodroplets dispersed in aqueous mixtures of functionalized hydrophilic polymer (polyethylene glycol diacrylate, PEGDA) and ionic surfactant (sodium dodecyl sulfate, SDS). Combining calorimetry, rheology and scattering measurements, we show how molecular self-assembly in the system can be used to control the viscoelasticity of the system, which remarkably follows time-temperature superposition, much like simpler polymer fluids, and suggests that polymer-surfactant complexation forms a transient polymer network between droplets. Systematic changes in the energy scale for complexation allows us to develop a simple model for the modulus and viscoelastic relaxation time. Furthermore, the relaxation time of the network in this model system can be varied by ten orders of magnitudes, providing advantages for fundamental studies.We exploited the properties of this novel nanoemulsion system to study shear-induced clustering of colloid-polymer mixtures and its impact on fluid rheology. The system allows us to explore several limiting regimes of polymer and suspension dynamics. Combining rheological characterization with three-dimensionally-resolved flow-small angle neutron scattering measurements reveals that an excess of particle fluxes along compressional and vorticity axes of shear are the primary mechanism of clustering, and suggestes that short-range hydrodynamic forces dominate the clustering of Brownian suspensions in viscoelastic fluids.Lastly, we used the thermoresponsive nanoemulsions to investigate the mechanisms of so-called “two-step” or “delayed” yielding in heterogeneous colloidal gels. At high temperatures, the model system forms colloidal gels with heterogeneous microstructure resembling arrested phase separation at elevated temperature caused by polymer-bridging interactions. Analyzing the sequence of mechanical processes during the intracycle yielding processes elucidates the detailed mechanism of frequency and strain amplitude-dependence of nonlinearlity. The nonlinear analysis also allows for characterization of the strain amplitude and rate-dependent yield stress and strain of the material. Furthermore, combining large amplitude oscillatory shear measuremetns with simultaneous small and ultra-small angle neutron scattering reveals that, contrary to previous hypotheses, large-scale microstructural processes play an important, if not dominant, role in the yielding of heterogeneous colloidal gels. The results of this thesis demonstrate that the rheology and the microstructural processes of nanoemulsions can be controlled through thermoresponsive polymer-surfactant-droplet association, which provides for sophisticated tuning of polymer-colloid and colloid-colloid interactions and dynamics, thus providing new routes and design rules for engineering the colloidal behavior of nanoemulsions

A Feature-Based Lexicalized Tree Adjoining Grammar for Korean

This document describes an on-going project of developing a grammar of Korean, the Korean XTAG grammar, written in the TAG formalism and implemented for use with the XTAG system enriched with a Korean morphological analyzer. The Korean XTAG grammar described in this report is based on the TAG formalism (Joshi et al. (1975)), which has been extended to include lexicalization (Schabes et al. (1988)), and unification-based feature structures (Vijay-Shanker and Joshi (1991)). The document first describes the modifications that we have made to the XTAG system (The XTAG-Group (1998)) to handle rich inflectional morphology in Korean. Then various syntactic phenomena that can be currently handled are described, including adverb modification, relative clauses, complex noun phrases, auxiliary verb constructions, gerunds and adjunct clauses. The work reported here is a first step towards the development of an implemented TAG grammar for Korean, which is continuously updated with the addition of new analyses and modification of old ones

Differential Cytokine Utilization and Tissue Tropism Results in Distinct Repopulation Kinetics of Naïve vs. Memory T Cells in Mice

Naïve and memory T cells co-exist in the peripheral T cell pool, but the cellular mechanisms that maintain the balance and homeostasis of these two populations remain mostly unclear. To address this question, here, we assessed homeostatic proliferation and repopulation kinetics of adoptively transferred naïve and memory T cells in lymphopenic host mice. We identified distinct kinetics of proliferation and tissue-distribution between naïve and memory donor T cells, which resulted in the occupancy of the peripheral T cell pool by mostly naïve-origin T cells in short term (<1 week), but, in a dramatic reversal, by mostly memory-origin T cells in long term (>4 weeks). To explain this finding, we assessed utilization of the homeostatic cytokines IL-7 and IL-15 by naïve and memory T cells. We found different efficiencies of IL-7 signaling between naïve and memory T cells, where memory T cells expressed larger amounts of IL-7Rα but were significantly less potent in activation of STAT5 that is downstream of IL-7 signaling. Nonetheless, memory T cells were superior in long-term repopulation of the peripheral T cell pool, presumably, because they preferentially migrated into non-lymphoid tissues upon adoptive transfer and additionally utilized tissue IL-15 for rapid expansion. Consequently, co-utilization of IL-7 and IL-15 provides memory T cells a long-term survival advantage. We consider this mechanism important, as it permits the memory T cell population to be maintained in face of constant influx of naïve T cells to the peripheral T cell pool and under competing conditions for survival cytokines

Association of proteinuria and incident atrial fibrillation in patients with diabetes mellitus: a population-based senior cohort study (vol 11, 17013, 2021)

The original version of this Article contained an error in the Funding section. “This study was supported by a research grant from the Korean Healthcare Technology R&D project funded by the Ministry of Health and Welfare (HI15C1200, HC19C0130) and a CMB-Yuhan research grant of Yonsei University College of Medicine (6-2019-0124).” now reads: “This study was supported by a research grant from the Korean Healthcare Technology R&D project funded by the Ministry of Health and Welfare (HI15C1200, HC19C0130, HI19C0622) and a CMB-Yuhan research grant of Yonsei University College of Medicine (6-2019-0124).” The original Article has been corrected