Towards Single-Channel Speech Separation in Noise and Reverberation

Many speech technologies, such as automatic speech recognition and speaker identification, are conventionally designed to only work on single speech streams. As a result, these systems can suffer severely degraded performance in cases of overlapping speech, i.e. when two or more people are speaking at the same time. Speech separation systems aim to address this problem by taking a recording of a speech mixture and outputting a single recording for each speaker in the mixture, where the interfering speech has been removed. The advancements in speech technology provided by deep neural networks have extended to speech separation, resulting in the first effectively functional single-channel speech separation systems. As performance of these systems has improved, there has been a desire to extend their capabilities beyond the clean studio recordings using close-talking microphones that the technology was initially developed on. In this dissertation, we focus on the extension of these technologies to the noisy and reverberant conditions more representative of real-world applications. Contributions of this dissertation include producing and releasing new data appropriate for training and evaluation of single-channel speech separation techniques, performing benchmark experiments to establish the degradation of conventional methods in more realistic settings, theoretical analysis of the impact, and development of new techniques targeted at improving system performance in these adverse conditions

Performance of Comorbidity, Risk Adjustment, and Functional Status Measures in Expenditure Prediction for Patients With Diabetes

OBJECTIVE—To compare the ability of generic comorbidity and risk adjustment measures, a diabetes-specific measure, and a self-reported functional status measure to explain variation in health care expenditures for individuals with diabetes

Patient perspectives on having multiple versus single prescribers of chronic disease medications: results of a qualitative study in a veteran population

BackgroundPatients with multiple chronic conditions often have multiple prescribers, which has been associated with greater health care utilization and medication nonadherence in claims-based analyses. This qualitative study was conducted to understand the reasons why patients have increasing numbers of prescribers of medications and to understand patient perspectives on advantages and disadvantages of having multiple prescribers, including effects on medication supply.MethodsThis qualitative study involved three focus groups comprising 23 outpatients from a single Veterans Affairs (VA) Medical Center with at least one chronic cardiometabolic condition (hypertension, diabetes, dyslipidemia, or congestive heart failure). Participants were asked about their experiences, including perceived of advantages and disadvantages, of having multiple prescribers of cardiometabolic medications. Conventional content analysis was used to analyze the data.ResultsMultiple prescribers arose through referrals and patients actively seeking non-VA prescribers (primary care and/or specialist) to maximize timeliness and access to medications, provide access to medications not on the VA formulary, and minimize out-of-pocket costs. Patients seeking non-VA care had to coordinate own their care by sharing prescriptions and test results to their prescribers within and outside VA.ConclusionsPrescribing physicians should engage in open dialogue with patients to create a shared understanding of patient and provider goals and priorities for chronic disease medications

Cinema Darkroom: A Deferred Rendering Framework for Large-Scale Datasets

This paper presents a framework that fully leverages the advantages of a deferred rendering approach for the interactive visualization of large-scale datasets. Geometry buffers (G-Buffers) are generated and stored in situ, and shading is performed post hoc in an interactive image-based rendering front end. This decoupled framework has two major advantages. First, the G-Buffers only need to be computed and stored once---which corresponds to the most expensive part of the rendering pipeline. Second, the stored G-Buffers can later be consumed in an image-based rendering front end that enables users to interactively adjust various visualization parameters---such as the applied color map or the strength of ambient occlusion---where suitable choices are often not known a priori. This paper demonstrates the use of Cinema Darkroom on several real-world datasets, highlighting CD's ability to effectively decouple the complexity and size of the dataset from its visualization

The CHiME-7 DASR Challenge: Distant Meeting Transcription with Multiple Devices in Diverse Scenarios

The CHiME challenges have played a significant role in the development and evaluation of robust automatic speech recognition (ASR) systems. We introduce the CHiME-7 distant ASR (DASR) task, within the 7th CHiME challenge. This task comprises joint ASR and diarization in far-field settings with multiple, and possibly heterogeneous, recording devices. Different from previous challenges, we evaluate systems on 3 diverse scenarios: CHiME-6, DiPCo, and Mixer 6. The goal is for participants to devise a single system that can generalize across different array geometries and use cases with no a-priori information. Another departure from earlier CHiME iterations is that participants are allowed to use open-source pre-trained models and datasets. In this paper, we describe the challenge design, motivation, and fundamental research questions in detail. We also present the baseline system, which is fully array-topology agnostic and features multi-channel diarization, channel selection, guided source separation and a robust ASR model that leverages self-supervised speech representations (SSLR)

Control Outcomes and Exposures for Improving Internal Validity of Nonrandomized Studies

Control outcomes and exposures can improve internal validity of nonrandomized studies by assessing residual bias in effect estimates. Control outcomes are those expected to have no treatment effect or the opposite effect of the primary outcome. Control exposures are treatments expected to have no effect on the primary outcome. We review examples of control outcomes and exposures from prior studies and provide recommendations for conducting and reporting these analyses

Continuity of medication management in Medicaid patients with chronic comorbid conditions: An examination by mental health status

Patients with serious mental illness (SMI) often have comorbid cardiometabolic conditions (CMCs) that may increase the number of prescribers involved in treatment. This study examined whether patients with SMI (depression and schizophrenia) and comorbid CMCs experience greater discontinuity of prescribing than patients with CMCs alone

Impacts of Geographic Distance on Peritoneal Dialysis Utilization: Refining Models of Treatment Selection

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/136011/1/hesr12489.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/136011/2/hesr12489-sup-0001-AuthorMatrix.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/136011/3/hesr12489_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/136011/4/hesr12489-sup-0002-Appendix.pd