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This thesis is a study of the production of human speech sounds by acoustic modelling and signal analysis. It concentrates on sounds that are not produced by voicing (although that may be present), namely plosives, fricatives and aspiration, which all contain noise generated by flow turbulence. It combines the application of advanced speech analysis techniques with acoustic flow-duct modelling of the vocal tract, and draws on dynamic magnetic resonance image (dMRI) data of the pharyngeal and oral cavities, to relate the sounds to physical shapes. Having superimposed vocal-tract outlines on three sagittal dMRI slices of an adult male subject, a simple description of the vocal tract suitable for acoustic modelling was derived through a sequence of transformations. The vocal-tract acoustics program VOAC, which relaxes many of the assumptions of conventional plane-wave models, incorporates the effects of net flow into a one-dimensional model (viz., flow separation, increase of entropy, and changes to resonances), as well as wall vibration and cylindrical wavefronts. It was used for synthesis by computing transfer functions from sound sources specified within the tract to the far field. Being generated by a variety of aero-acoustic mechanisms, unvoiced sounds are somewhat varied in nature. Through analysis that was informed by acoustic modelling, resonance and anti-resonance frequencies of ensemble-averaged plosive spectra were examined for the same subject, and their trajectories observed during release. The anti-resonance frequencies were used to compute the place of occlusion. In vowels and voiced fricatives, voicing obscures the aspiration and frication components. So, a method was devised to separate the voiced and unvoiced parts of a speech signal, the pitch-scaled harmonic filter (PSHF), which was tested extensively on synthetic signals. Based on a harmonic model of voicing, it outputs harmonic and anharmonic signals appropriate for subsequent analysis as time series or as power spectra. By applying the PSHF to sustained voiced fricatives, we found that, not only does voicing modulate the production of frication noise, but that the timing of pulsation cannot be explained by acoustic propagation alone. In addition to classical investigation of voiceless speech sounds, VOAC and the PSHF demonstrated their practical value in helping further to characterise plosion, frication and aspiration noise. For the future, we discuss developing VOAC within an articulatory synthesiser, investigating the observed flow-acoustic mechanism in a dynamic physical model of voiced frication, and applying the PSHF more widely in the field of speech research.

No / Hemp concrete is an attractive alternative to traditional materials used in building construction. It has a very low environmental impact, and it is characterized by high thermal insulation. Hemp aggregate particles are parallelepiped in shape and can be organized in a plurality of ways to create a considerable proportion of open pores with a complex connectivity pattern, the acoustical properties of which have never been examined systematically. Therefore this paper is focused on the fundamental understanding of the relations between the particle shape and size distribution, pore size distribution, and the acoustical properties of the resultant porous material mixture. The sound absorption and the transmission loss of various hemp aggregates is characterized using laboratory experiments and three theoretical models. These models are used to relate the particle size distribution to the pore size distribution. It is shown that the shape of particles and particle size control the pore size distribution and tortuosity in shiv. These properties in turn relate directly to the observed acoustical behavior.

No / Graded porous materials are of growing interest because of their ability to improve the impedance matching between air and material itself. Theoretical models have been developed to predict the acoustical properties of these media. Traditionally, graded materials have been manufactured by stacking a discrete number of homogeneous porous layers with different pore microstructure. More recently a novel foaming process for the manufacturing of porous materials with continuous pore stratification has been developed. This paper reports on the application of the numerical procedure proposed by De Ryck to invert the parameters of the pore size distribution from the impedance tube measurements for materials with continuously stratified pore microstructure. Specifically, this reconstruction procedure has been successfully applied to retrieve the flow resistivity and tortuosity profiles of graded porous materials manufactured with the method proposed by Mahasaranon et al. In this work the porosity and standard deviation in pore size are assumed constant and measured using methods which are applied routinely for homogenous materials characterisation. The numerical method is based on the wave splitting together with the transmission Green's functions approach, yielding an analytical expression of the objective function in the Least-square sense.

The increased use of the diesel engine in the passenger car, truck and bus market is due to high efficiency and lower fuel costs. This growing market share has brought with it several environmental issues for instance soot particle emission. Different technologies to remove the soot have been developed and are normally based on some kind of soot trap. In particular for automobiles the use of diesel particulate traps or filters (DPF:s) based on ceramic monolithic honeycombs are becoming a standard. This new exhaust system component will affect the acoustics and also work as a muffler. To properly design exhaust systems acoustic models for diesel particulate traps are needed. The first part of this thesis considers the modelling of sound transmission and attenuation for traps that consist of narrow channels separated by porous walls. This work has resulted in two new models an approximate 1-D model and a more complete model based on the governing equations for a visco-thermal fluid. Both models are expressed as acoustic 2-ports which makes them suitable for implementation in acoustic software for exhaust systems analysis. The models have been validated by experiments on clean filters at room temperature with flow and the agreement is good. In addition the developed filter models have been used to set up a model for a complete After Treatment Device (ATD) for a passenger car. The unit consisted of a chamber which contained both a diesel trap and a Catalytic Converter (CC). This complete model was also validated by experiments at room temperature. The second part of the thesis focuses on experimental techniques for plane wave decomposition in ducts with flow. Measurements in ducts with flow are difficult since flow noise (turbulence) can strongly influence the data. The difficulties are also evident from the lack of good published in-duct measurement data, e.g., muffler transmission loss data, for Mach-numbers above 0.1-0.2. The first paper in this part of the thesis investigates the effect of different microphone mountings and signal processing techniques for suppressing flow noise. The second paper investigates in particular flow noise suppression techniques in connection with the measurement of acoustic 2-ports. Finally, the third paper suggests a general wave decomposition procedure using microphone arrays and over-determination. This procedure can be used to determine the full plane wave data, e.g., the wave amplitudes and complex wave numbers k+ and k-. The new procedure has been applied to accurately measure the sound radiation from an unflanged pipe with flow. This problem is of interest for correctly determining the radiated power from an engine exhaust outlet. The measured data for the reflection coefficient and end correction have been compared with the theory of Munt [33] and the agreement is excellent. The measurements also produced data for the damping value (imaginary part of the wavenumber) which were compared to a model suggested by Howe [13]. The agreement is good for a normalized boundary layer thickness less than 30-40

<p>The increased use of the diesel engine in the passenger car, truck and bus market is due to high efficiency and lower fuel costs. This growing market share has brought with it several environmental issues for instance soot particle emission. Different technologies to remove the soot have been developed and are normally based on some kind of soot trap. In particular for automobiles the use of diesel particulate traps or filters (DPF:s) based on ceramic monolithic honeycombs are becoming a standard. This new exhaust system component will affect the acoustics and also work as a muffler. To properly design exhaust systems acoustic models for diesel particulate traps are needed. The first part of this thesis considers the modelling of sound transmission and attenuation for traps that consist of narrow channels separated by porous walls. This work has resulted in two new models an approximate 1-D model and a more complete model based on the governing equations for a visco-thermal fluid. Both models are expressed as acoustic 2-ports which makes them suitable for implementation in acoustic software for exhaust systems analysis. The models have been validated by experiments on clean filters at room temperature with flow and the agreement is good. In addition the developed filter models have been used to set up a model for a complete After Treatment Device (ATD) for a passenger car. The unit consisted of a chamber which contained both a diesel trap and a Catalytic Converter (CC). This complete model was also validated by experiments at room temperature. The second part of the thesis focuses on experimental techniques for plane wave decomposition in ducts with flow. Measurements in ducts with flow are difficult since flow noise (turbulence) can strongly influence the data. The difficulties are also evident from the lack of good published in-duct measurement data, e.g., muffler transmission loss data, for Mach-numbers above 0.1-0.2. The first paper in this part of the thesis investigates the effect of different microphone mountings and signal processing techniques for suppressing flow noise. The second paper investigates in particular flow noise suppression techniques in connection with the measurement of acoustic 2-ports. Finally, the third paper suggests a general wave decomposition procedure using microphone arrays and over-determination. This procedure can be used to determine the full plane wave data, e.g., the wave amplitudes and complex wave numbers k+ and k-. The new procedure has been applied to accurately measure the sound radiation from an unflanged pipe with flow. This problem is of interest for correctly determining the radiated power from an engine exhaust outlet. The measured data for the reflection coefficient and end correction have been compared with the theory of Munt [33] and the agreement is excellent. The measurements also produced data for the damping value (imaginary part of the wavenumber) which were compared to a model suggested by Howe [13]. The agreement is good for a normalized boundary layer thickness less than 30-40</p>

Unsupervised learning of speech is concerned with automatically finding patterns such as words or speech sounds, without supervision in the form of orthographical transcriptions or a priori knowledge of the language. However, a fundamental problem is that unsupervised speech learning methods tend to discover highly speaker-specific and context-dependent representations of speech. We propose a method for improving the quality of posteriorgrams generated from an unsupervised model through partitioning of the latent classes discovered by the model. We do this by training a sparse siamese model to find a linear transformation of input posteriorgrams, extracted from the unsupervised model, to lower-dimensional posteriorgrams. The siamese model makes use of same-category and different-category speech fragment pairs obtained through unsupervised term discovery. After training, the model is converted into an exact partitioning of the posteriorgrams. We evaluate the model on the minimal-pair ABX task in the context of the Zero Resource Speech Challenge. We are able to demonstrate that our method significantly reduces the dimensionality of standard Gaussian mixture model posteriorgrams, while also making them more speaker invariant. This suggests that the model may be viable as a general post-processing step to improve probabilistic acoustic features obtained by unsupervised learning. / Obevakad inlärning av tal innebär att automatiskt hitta mönster i tal, t ex ord eller talljud, utan bevakning i form av ortografiska transkriptioner eller tidigare kunskap om språket. Ett grundläggande problem är dock att obevakad talinlärning tenderar att hitta väldigt talar- och kontextspecifika representationer av tal. Vi föreslår en metod för att förbättra kvaliteten av posteriorgram genererade med en obevakad modell, genom att partitionera de latenta klasserna funna av modellen. Vi gör detta genom att träna en gles siamesisk modell för att hitta en linjär transformering av de givna posteriorgrammen, extraherade från den obevakade modellen, till lågdimensionella posteriorgram. Den siamesiska modellen använder sig av talfragmentpar funna med obevakad ordupptäckning, där varje par består av fragment som antingen tillhör samma eller olika klasser. Den färdigtränade modellen görs sedan om till en exakt partitionering av posteriorgrammen. Vi följer Zero Resource Speech Challenge, och evaluerar modellen med hjälp av minimala ordpar-ABX-uppgiften. Vi demonstrerar att vår metod avsevärt minskar posteriorgrammens dimensionalitet, samtidigt som posteriorgrammen blir mer talarinvarianta. Detta antyder att modellen kan vara användbar som ett generellt extra steg för att förbättra probabilistiska akustiska särdrag från obevakade modeller.

Electrical stimulation of the retina affected by photoreceptor loss (e.g., cases of retinitis pigmentosa) elicits the perception of luminous spots (so-called phosphenes) in the visual field. This phenomenon, attributed to the relatively high survival rates of neurons comprising the retina's inner layer, serves as the cornerstone of efforts to provide a microelectronic retinal prosthesis -- a device analogous to the cochlear implant. This thesis concerns phosphenes -- their elicitation and modulation, and, in turn, image analysis for use in a prosthesis. This thesis begins with a comparative review of visual modelling of electrical epiretinal stimulation and analogous acoustic modelling of electrical cochlear stimulation. The latter models involve coloured noise played to normal listeners so as to investigate speech processing and electrode design for use in cochlear implants. Subsequently, four experiments (three psychophysical and one numerical), and two statistical analyses, are presented. Intrinsic signal optical imaging in cerebral cortex is canvassed appendically. The first experiment describes a visual tracking task administered to 20 normal observers afforded simulated prosthetic vision. Fixation, saccade, and smooth pursuit, and the effect of practice, were assessed. Further, an image analysis scheme is demonstrated that, compared to existing approaches, assisted fixation and pursuit (but not saccade) accuracy (35.8% and 6.8%, respectively), and required less phosphene array scanning. Subsequently, (numerical) information-theoretic reasoning is provided for the scheme's superiority. This reasoning was then employed to further optimise the scheme (resulting in a filter comprising overlapping Gaussian kernels), and may be readily extended to arbitrary arrangements of many phosphenes. A face recognition study, wherein stimuli comprised either size- or intensity-modulated phosphenes, is then presented. The study involved unpracticed observers (n=85), and showed no 'size' --versus--'intensity' effect. Overall, a 400-phosphene (100-phosphene) image afforded subjects 89.0% (64.0%) correct recognition (two-interval forced-choice paradigm) when five seconds' scanning was allowed. Performance fell (64.5%) when the 400-phosphene image was stabilised on the retina and presented briefly. Scanning was similar in 400- and 100-phosphene tasks. The final chapter presents the statistical effects of sampling and rendering jitter on the phosphene image. These results may generalise to low-resolution imaging systems involving loosely packed pixels.

Electrical stimulation of the retina affected by photoreceptor loss (e.g., cases of retinitis pigmentosa) elicits the perception of luminous spots (so-called phosphenes) in the visual field. This phenomenon, attributed to the relatively high survival rates of neurons comprising the retina's inner layer, serves as the cornerstone of efforts to provide a microelectronic retinal prosthesis -- a device analogous to the cochlear implant. This thesis concerns phosphenes -- their elicitation and modulation, and, in turn, image analysis for use in a prosthesis. This thesis begins with a comparative review of visual modelling of electrical epiretinal stimulation and analogous acoustic modelling of electrical cochlear stimulation. The latter models involve coloured noise played to normal listeners so as to investigate speech processing and electrode design for use in cochlear implants. Subsequently, four experiments (three psychophysical and one numerical), and two statistical analyses, are presented. Intrinsic signal optical imaging in cerebral cortex is canvassed appendically. The first experiment describes a visual tracking task administered to 20 normal observers afforded simulated prosthetic vision. Fixation, saccade, and smooth pursuit, and the effect of practice, were assessed. Further, an image analysis scheme is demonstrated that, compared to existing approaches, assisted fixation and pursuit (but not saccade) accuracy (35.8% and 6.8%, respectively), and required less phosphene array scanning. Subsequently, (numerical) information-theoretic reasoning is provided for the scheme's superiority. This reasoning was then employed to further optimise the scheme (resulting in a filter comprising overlapping Gaussian kernels), and may be readily extended to arbitrary arrangements of many phosphenes. A face recognition study, wherein stimuli comprised either size- or intensity-modulated phosphenes, is then presented. The study involved unpracticed observers (n=85), and showed no 'size' --versus--'intensity' effect. Overall, a 400-phosphene (100-phosphene) image afforded subjects 89.0% (64.0%) correct recognition (two-interval forced-choice paradigm) when five seconds' scanning was allowed. Performance fell (64.5%) when the 400-phosphene image was stabilised on the retina and presented briefly. Scanning was similar in 400- and 100-phosphene tasks. The final chapter presents the statistical effects of sampling and rendering jitter on the phosphene image. These results may generalise to low-resolution imaging systems involving loosely packed pixels.