Investigating the shortcomings of HMM synthesis

This paper presents the beginnings of a framework for formal testing of the causes of the current limited quality of HMM (Hidden Markov Model) speech synthesis. This framework separates each of the effects of modelling to observe their independent effects on vocoded speech parameters in order to address the issues that are restricting the progression to highly intelligible and natural-sounding speech synthesis. The simulated HMM synthesis conditions are performed on spectral speech parameters and tested via a pairwise listening test, asking listeners to perform a “same or different ” judgement on the quality of the synthesised speech produced between these conditions. These responses are then processed using multidimensional scaling to identify the qualities in modelled speech that listeners are attending to and thus forms the basis of why they are distinguishable from natural speech. The future improvements to be made to the framework will finally be discussed which include the extension to more of the parameters modelled during speech synthesis

A Key to Container-Breeding Mosquitoes of Michigan (Diptera: Cllllcidae), With Notes on Their Biology

An illustrated key to larvae and notes on the biology of container-breeding mosquitoes of Michigan are presented. Two species included in the key. Aedes aegypti and Aedes albopictus. are not endemic in Michigan, but occasional introductions could occur with commercial shipments of scrap tires or other containers

The Chicago and eastern Illinois railroad yards

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A theoretical determination of lattice energy, lattice constant and compressibility of metallic copper and silver

This item was digitized by the Internet Archive

ALIGNING USAF STUDENT RESEARCH WITH STRATEGIC PRIORITIES

The United States Air Force (USAF) is not effectively utilizing the student research ecosystem to contribute toward USAF strategic priorities. This project researched how the USAF can enhance student research to contribute toward senior leaders’ requirements. The USAF needs to align academic research to provide solutions toward strategic competition in a resource-constrained environment. Aligning research to problems can only enhance the resulting innovation. We submitted a survey to 1,175 USAF students at civilian institutions. Of 266 responses, 83% had a deliverable requirement, 81% did not receive information about current USAF research priorities and funding opportunities, 91% would have considered incorporating USAF research priorities into their graduate research if they had received information about them, and 95% would potentially use a mobile application that gives access to prioritized USAF research questions, command sponsorships, and funding. Not aligning USAF-sponsored academic research with strategic priorities is mainly an organizational problem. First, the USAF should improve the talent management process to match students to appropriate research fields. Second, the USAF should improve education about academic resources for aligning research, finding sponsors, and securing funding. Lastly, the USAF should connect existing AFIT/CI students across the research ecosystem via a mobile application endorsed by Air Education and Training Command.Lieutenant Colonel, United States Air ForceMajor, United States Air ForceApproved for public release. Distribution is unlimited

Arctic fires re-emerging

Underground smouldering fires resurfaced early in 2020, contributing to the unprecedented wildfires that tore through the Arctic this spring and summer. An international effort is needed to manage a changing fire regime in the vulnerable Arctic

Overcoming the limitations of statistical parametric speech synthesis

At the time of beginning this thesis, statistical parametric speech synthesis (SPSS) using hidden Markov models (HMMs) was the dominant synthesis paradigm within the research community. SPSS systems are effective at generalising across the linguistic contexts present in training data to account for inevitable unseen linguistic contexts at synthesis-time, making these systems flexible and their performance stable. However HMM synthesis suffers from a ‘ceiling effect’ in the naturalness achieved, meaning that, despite great progress, the speech output is rarely confused for natural speech. There are many hypotheses for the causes of reduced synthesis quality, and subsequent required improvements, for HMM speech synthesis in literature. However, until this thesis, these hypothesised causes were rarely tested. This thesis makes two types of contributions to the field of speech synthesis; each of these appears in a separate part of the thesis. Part I introduces a methodology for testing hypothesised causes of limited quality within HMM speech synthesis systems. This investigation aims to identify what causes these systems to fall short of natural speech. Part II uses the findings from Part I of the thesis to make informed improvements to speech synthesis. The usual approach taken to improve synthesis systems is to attribute reduced synthesis quality to a hypothesised cause. A new system is then constructed with the aim of removing that hypothesised cause. However this is typically done without prior testing to verify the hypothesised cause of reduced quality. As such, even if improvements in synthesis quality are observed, there is no knowledge of whether a real underlying issue has been fixed or if a more minor issue has been fixed. In contrast, I perform a wide range of perceptual tests in Part I of the thesis to discover what the real underlying causes of reduced quality in HMM synthesis are and the level to which they contribute. Using the knowledge gained in Part I of the thesis, Part II then looks to make improvements to synthesis quality. Two well-motivated improvements to standard HMM synthesis are investigated. The first of these improvements follows on from averaging across differing linguistic contexts being identified as a major contributing factor to reduced synthesis quality. This is a practice typically performed during decision tree regression in HMM synthesis. Therefore a system which removes averaging across differing linguistic contexts and instead performs averaging only across matching linguistic contexts (called rich-context synthesis) is investigated. The second of the motivated improvements follows the finding that the parametrisation (i.e., vocoding) of speech, standard practice in SPSS, introduces a noticeable drop in quality before any modelling is even performed. Therefore the hybrid synthesis paradigm is investigated. These systems aim to remove the effect of vocoding by using SPSS to inform the selection of units in a unit selection system. Both of the motivated improvements applied in Part II are found to make significant gains in synthesis quality, demonstrating the benefit of performing the style of perceptual testing conducted in the thesis

Regularizing made-to-measure particle models of galaxies

Made-to-measure methods such as the parallel code NMAGIC are powerful tools to build galaxy models reproducing observational data. They work by adapting the particle weights in an N-body system until the target observables are well matched. Here we introduce a moving prior regularization (MPR) method for such particle models. It is based on determining from the particles a distribution of priors in phase-space, which are updated in parallel with the weight adaptation. This method allows one to construct smooth models from noisy data without erasing global phase-space gradients. We first apply MPR to a spherical system for which the distribution function can in theory be uniquely recovered from idealized data. We show that NMAGIC with MPR indeed converges to the true solution with very good accuracy, independent of the initial particle model. Compared to the standard weight entropy regularization, biases in the anisotropy structure are removed and local fluctuations in the intrinsic distribution function are reduced. We then investigate how the uncertainties in the inferred dynamical structure increase with less complete and noisier kinematic data, and how the dependence on the initial particle model also increases. Finally, we apply the MPR technique to the two intermediate-luminosity elliptical galaxies NGC 4697 and NGC 3379, obtaining smoother dynamical models in luminous and dark matter potentials.Comment: 16 pages, 15 figures, 2 tables. Accepted for publication in MNRA