Glottal-synchronous speech processing

Glottal-synchronous speech processing is a field of speech science where the pseudoperiodicity of voiced speech is exploited. Traditionally, speech processing involves segmenting and processing short speech frames of predefined length; this may fail to exploit the inherent periodic structure of voiced speech which glottal-synchronous speech frames have the potential to harness. Glottal-synchronous frames are often derived from the glottal closure instants (GCIs) and glottal opening instants (GOIs). The SIGMA algorithm was developed for the detection of GCIs and GOIs from the Electroglottograph signal with a measured accuracy of up to 99.59%. For GCI and GOI detection from speech signals, the YAGA algorithm provides a measured accuracy of up to 99.84%. Multichannel speech-based approaches are shown to be more robust to reverberation than single-channel algorithms. The GCIs are applied to real-world applications including speech dereverberation, where SNR is improved by up to 5 dB, and to prosodic manipulation where the importance of voicing detection in glottal-synchronous algorithms is demonstrated by subjective testing. The GCIs are further exploited in a new area of data-driven speech modelling, providing new insights into speech production and a set of tools to aid deployment into real-world applications. The technique is shown to be applicable in areas of speech coding, identification and artificial bandwidth extension of telephone speec

Joint ventures in the cable and videotex industries

Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1984.MICROFICHE COPY AVAILABLE IN ARCHIVES AND DEWEY.Bibliography: leaves 202-213.by Thomas P. Caruso and Mark R. Harsch.M.S

Do jumbo-CD holders care about anything?

Uninsured deposits represent a theoretically appealing but relatively untested alternative to subordinated debt for incorporating market discipline into banking supervision. To make the deposit market a useful supervisory tool, it is necessary to know what types of risk are priced by depositors and in what proportions. Using a clustering technique to select from among a large set of potential regressors, as well as a carefully chosen set of control variables, we attempt to determine the types of risk that cause uninsured depositors to react in both the price and quantity dimensions. As a benchmark for economic significance, we estimate similar regressions on supervisory ratings. We find that, in contrast to government supervisors, depositors have not priced most types of risk since 1997. Indeed, the only risk variables that consistently come up as statistically significant are those that measure capital adequacy. Our interpretation of these results is that, because aggregate banking conditions are good, it is not worth depositors' effort to investigate individual bank quality very carefully. We conclude that, in the current economic and regulatory environment, the market is content to delegate most of its monitoring and discipline to the government. To the extent that it does monitor, it only monitors capital. The jumbo-CD market is thus not likely to be of much supervisory use, particularly given that examiners already have good information about capital levels. The depositor emphasis on capital also supports the conjecture that market discipline was responsible for much of the recent capital build-up.Bank deposits ; Bank supervision

Composition and concentration anomalies for structure and dynamics of Gaussian-core mixtures

We report molecular dynamics simulation results for two-component fluid mixtures of Gaussian-core particles, focusing on how tracer diffusivities and static pair correlations depend on temperature, particle concentration, and composition. At low particle concentrations, these systems behave like simple atomic mixtures. However, for intermediate concentrations, the single-particle dynamics of the two species largely decouple, giving rise to the following anomalous trends. Increasing either the concentration of the fluid (at fixed composition) or the mole fraction of the larger particles (at fixed particle concentration) enhances the tracer diffusivity of the larger particles, but decreases that of the smaller particles. In fact, at sufficiently high particle concentrations, the larger particles exhibit higher mobility than the smaller particles. Each of these dynamic behaviors is accompanied by a corresponding structural trend that characterizes how either concentration or composition affects the strength of the static pair correlations. Specifically, the dynamic trends observed here are consistent with a single empirical scaling law that relates an appropriately normalized tracer diffusivity to its pair-correlation contribution to the excess entropy.Comment: 5 pages, 4 figure

Bubble Raft Model for a Paraboloidal Crystal

We investigate crystalline order on a two-dimensional paraboloid of revolution by assembling a single layer of millimeter-sized soap bubbles on the surface of a rotating liquid, thus extending the classic work of Bragg and Nye on planar soap bubble rafts. Topological constraints require crystalline configurations to contain a certain minimum number of topological defects such as disclinations or grain boundary scars whose structure is analyzed as a function of the aspect ratio of the paraboloid. We find the defect structure to agree with theoretical predictions and propose a mechanism for scar nucleation in the presence of large Gaussian curvature.Comment: 4 pages, 4 figure

Small‐scale structure of the midlatitude storm enhanced density plume during the 17 March 2015 St. Patrick’s Day storm

Kilometer‐scale density irregularities in the ionosphere can cause ionospheric scintillation—a phenomenon that degrades space‐based navigation and communication signals. During strong geomagnetic storms, the midlatitude ionosphere is primed to produce these ∼1–10 km small‐scale irregularities along the steep gradients between midlatitude storm enhanced density (SED) plumes and the adjacent low‐density trough. The length scales of irregularities on the order of 1–10 km are determined from a combination of spatial, temporal, and frequency analyses using single‐station ground‐based Global Positioning System total electron content (TEC) combined with radar plasma velocity measurements. Kilometer‐scale irregularities are detected along the boundaries of the SED plume and depleted density trough during the 17 March 2015 geomagnetic storm, but not equatorward of the plume or within the plume itself. Analysis using the fast Fourier transform of high‐pass filtered slant TEC suggests that the kilometer‐scale irregularities formed near the poleward gradients of SED plumes can have similar intensity and length scales to those typically found in the aurora but are shown to be distinct phenomena in spacecraft electron precipitation measurements.Key PointsKilometer‐scale density irregularities measured in single‐station GPS TEC data from the 17 March 2015 storm enhanced density plume systemLocation, intensity, and length scales are estimated from spatial, temporal, and frequency analyses of multiple instrument dataFormation regions for small‐scale irregularities with length scales of 3‐10 km are identified for plasma velocities of 500–1200 m s−1Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136745/1/jgra53295_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136745/2/jgra53295.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136745/3/jgra53295-sup-0001-supplementary.pd

Voice SourceWaveform Analysis and Synthesis Using Principal Component Analysis and Gaussian Mixture Modelling

The paper presents a voice source waveform modeling techniques based on principal component analysis (PCA) and Gaussian mixture modeling (GMM). The voice source is obtained by inverse-filtering speech with the estimated vocal tract filter. This decomposition is useful in speech analysis, synthesis, recognition and coding. Here, a data-driven approach is presented for signal decomposition and classification based on the principal components of the voice source. The principal components are analyzed and the 'prototype' voice source signals corresponding to the Gaussian mixture means are examined. We show how an unknown signal can be decomposed into its components and/or prototypes and resynthesized. We show how the techniques are suited for both low bitrate or high quality analysis/synthesis schemes

Effect of Dietary Changes on Manure Nutrient Content and Value

The design of the model is to evaluate a more comprehensive valuation swine feeding programs other than cost per ton of feed or cost per pound of gain. Ingredient supplies and value may be part of the a production system, but if that system depends upon more than pounds of pork out the door, and utilizes manure as a fertilizer input for crop production, then how the pigs are fed has consequences other than feed cost per pig or gain. The model may be used to help identify the role of swine diet formulations in the determination of manure nutrient content and value. This is just one component within a crop to feed to fertilizer cycle, and there are other factors which may influence the nutrient concentrations in swine manure and manure samples need to be taken and analyzed prior to field application

Generalized Rosenfeld scalings for tracer diffusivities in not-so-simple fluids: Mixtures and soft particles

Rosenfeld [Phys. Rev. A 15, 2545 (1977)] noticed that casting transport coefficients of simple monatomic, equilibrium fluids in specific dimensionless forms makes them approximately single-valued functions of excess entropy. This has predictive value because, while the transport coefficients of dense fluids are difficult to estimate from first principles, excess entropy can often be accurately predicted from liquid-state theory. Here, we use molecular simulations to investigate whether Rosenfeld's observation is a special case of a more general scaling law relating mobility of particles in mixtures to excess entropy. Specifically, we study tracer diffusivities, static structure, and thermodynamic properties of a variety of one- and two-component model fluid systems with either additive or non-additive interactions of the hard-sphere or Gaussian-core form. The results of the simulations demonstrate that the effects of mixture concentration and composition, particle-size asymmetry and additivity, and strength of the interparticle interactions in these fluids are consistent with an empirical scaling law relating the excess entropy to a new dimensionless (generalized Rosenfeld) form of tracer diffusivity, which we introduce here. The dimensionless form of the tracer diffusivity follows from knowledge of the intermolecular potential and the transport / thermodynamic behavior of fluids in the dilute limit. The generalized Rosenfeld scaling requires less information, and provides more accurate predictions, than either Enskog theory or scalings based on the pair-correlation contribution to the excess entropy. As we show, however, it also suffers from some limitations, especially for systems that exhibit significant decoupling of individual component tracer diffusivities.Comment: 15 pages, 10 figure