GMM based Bayesian approach to speech enhancement in signal transform domain

Considering a general linear model of signal degradation, by modeling the probability density function (PDF) of the clean signal using a Gaussian mixture model (GMM) and additive noise by a Gaussian PDF, we derive the minimum mean square error (MMSE) estimator. The derived MMSE estimator is non-linear and the linear MMSE estimator is shown to be a special case. For speech signal corrupted by independent additive noise, by modeling the joint PDF of time-domain speech samples of a speech frame using a GMM, we propose a speech enhancement method based on the derived MMSE estimator. We also show that the same estimator can be used for transform-domain speech enhancement.

Communication and Political Crisis: Media, Politics and Governance in a Globalized Public Sphere

Communication and Political Crisis explores the role of the global media in a period of intensifying geopolitical conflict. Through case studies drawn from domestic and international political crises such as the conflicts in the Middle East and Ukraine, leading media scholar Brian McNair argues that the digitized, globalized public sphere now confronted by all political actors has produced new opportunities for social progress and democratic reform, as well as new channels for state propaganda and terrorist spectaculars such as those performed by the Islamic State and Al Qaeda. In this major work, McNair argues that the role of digital communication will be crucial in determining the outcome of pressing global issues such as the future of feminism and gay rights, freedom of speech and media, and democracy itself.

Comprehending adverbs of doubt and certainty in health communication: A multidimensional scaling approach

This research explored the feasibility of using multidimensional scaling (MDS) analysis in novel combination with other techniques to study comprehension of epistemic adverbs expressing doubt and certainty (e.g., evidently, obviously, probably) as they relate to health communication in clinical settings. In Study 1, Australian English speakers performed a dissimilarity-rating task with sentence pairs containing the target stimuli, presented as "doctors' opinions". Ratings were analyzed using a combination of cultural consensus analysis (factor analysis across participants), weighted-data classical-MDS, and cluster analysis. Analyses revealed strong within-community consistency for a 3-dimensional semantic space solution that took into account individual differences, strong statistical acceptability of the MDS results in terms of stress and explained variance, and semantic configurations that were interpretable in terms of linguistic analyses of the target adverbs. The results confirmed the feasibility of using MDS in this context. Study 2 replicated the results with Canadian English speakers on the same task. Semantic analyses and stress decomposition analysis were performed on the Australian and Canadian data sets, revealing similarities and differences between the two groups. Overall, the results support using MDS to study comprehension of words critical for health communication, including in future studies, for example, second language speaking patients and/or practitioners. More broadly, the results indicate that the techniques described should be promising for comprehension studies in many communicative domains, in both clinical settings and beyond, and including those targeting other aspects of language and focusing on comparisons across different speech communities.

Understanding data flow and security requirements in wireless Body Area Networks for healthcare

The Body Area Network (BAN) is an emerging technology that focuses on monitoring physiological data in, on and around the human body. BAN technology permits wearable and implanted sensors to collect vital data about the human body and transmit it to other nodes via low-energy communication. In this paper, we investigate interactions in terms of data flows between parties involved in BANs under four different scenarios targeting outdoor and indoor medical environments: hospital, home, emergency and open areas. Based on these scenarios, we identify data flow requirements between BAN elements such as sensors and control units (CUs) and parties involved in BANs such as the patient, doctors, nurses and relatives. Identified requirements are used to generate BAN data flow models. Petri Nets (PNs) are used as the formal modelling language. We check the validity of the models and compare them with the existing related work. Finally, using the models, we identify communication and security requirements based on the most common active and passive attack scenarios.

Mask or mirrors? The emergence of consumer rights in nonprofit human service organisations

This paper reports on a study of 25 nonprofit human service organisations offering four types of human services. The purpose of the study was first to explore the manner in which consumer rights are both conceptualized and operationalized in the nonprofit human service context. Secondly the study explored whether differences occur between organisations whose primary funding body emphasized the importance of a rights framework in its program delivery and those where this is not the case.

Personporträttet som tidningsgenre : En närläsningsstudie med fokus på innehållsliga teman, berättarkonventioner och kön

The thesis The portrait interview as a newspaper genre. A qualitative close reading focussing on topical motifs, conventions of narration, and gender defines the portrait interview as a newspaper genre and analyses how the personalities in the portraits are constructed textually. The main body of material consists of 107 portrait interviews in two morning newspapers, Dagens Nyheter (published in Stockholm, Sweden) and Hufvudstadsbladet (published in Swedish in Helsinki, Finland), during two one-week periods (week 46/1999 and week 38/2002). There is also complementary material of 59 portraits from four magazines. The study is carried out within the research traditions of journalistic genre studies, gender and journalism, and critical text analysis. It is comprised of a qualitative close reading focussing on content (topical motifs or themes), conventions of narration, and gender. The methods used to carry out the study are qualitative close reading and quantitative content analysis. The analysis identifies the stylistic elements that differentiate the portrait genre from other journalistic genres, as well as from the autobiographical genre, and explores what opportunities and limitations these elements present for the inclusion of even more women protagonists in the portrait genre. The portrait interview is an exception from the critical mission of journalism in general, with its position as a genre of politeness. Since a typical characteristic of the portrait interview genre is that it pays tribute to the protagonist, the genre reveals the kind of personalities and lives that are seen as admirable in society. Four levels of portrait interview are defined: the prototype portrait, the pure portrait, the hybrid portrait and the marginal portrait. The prototype is a raw version of a portrait that fulfils the criteria but may be lacking in content and stylistics. The pure portrait does not lack these qualities and resembles an ideal portrait. The hybrid is a borderline case which relates to another genre or is a mixture between the portrait and some other genre, most commonly the news genre. The marginal portrait does not fulfil the criteria, and can therefore be seen as an inadequate portrait. For example, obituaries and caricatures are excluded if the protagonist s voice is never quoted. The analysis resulted in three factors that in part help to explain why the portrait interview genre has somewhat more female protagonists than journalistic news texts do in general. The four main reasons why women are presented somewhat more in the portrait genre than in other journalistic genres are: (i) women are shown as exceptions to the female norm when, for example, taking a typical male job or managing in positions where there are few women; (ii) women are shown as representing female themes ; (iii) use of the double bind as a story-generating factor; and (iv) the intimisation of journalism. The double bind usually builds up the narration on female ambiguity in the contradiction between private and public life, for example family and career, personal desire and work. The intimisation of journalism and the double bind give women protagonists somewhat more publicity also because of the tendency of portrait interviews to create conflicts within the protagonist, as an exception to journalism in general where conflicts are created or seen as existing between, for example, persons, groupings or parties. Women protagonists and their lives create an optimal narration of inner conflicts originating in the double bind as men are usually not seen as suffering from these conflicts. The analysis also resulted in gendered portrait norms: The feminine portrait norm and the masculine portrait norm or more concretely, professional life and family life as expectation and exception. Women are expected to be responsible parents and mediocre professionals, while men are expected to be professionals and in their free time engaging fathers. Key words: journalism, genre, portrait interview, gender, interview, newspaper, women s magazine.

Construing and Defining the Out of Control : Addiction in the Media 1968-2008.

The four scientific articles comprising this doctoral dissertation offer new information on the presentation and construction of addiction in the mass media during the period 1968 - 2008. Diachronic surveys as well as quantitative and qualitative content analyses were undertaken to discern trends during the period in question and to investigate underlying conceptions of the problems in contemporary media presentations. The research material for the first three articles consists of a sample of 200 texts from Finland s biggest daily newspaper, Helsingin Sanomat, from the period 1968 - 2006. The fourth study examines English-language tabloid material published on the Internet in 2005 - 2008. A number of principal trends are identified. In addition to a significant increase in addiction reporting over time, the study shows that an internalisation of addiction problems took place in the media presentations under study. The phenomenon is portrayed and tackled from within the problems themselves, often from the viewpoint of the individuals concerned. The tone becomes more personal, and technical and detailed accounts are more and more frequent. Secondly, the concept of addiction is broadened. This can be dated to the 1990s. The concept undergoes a conventionalisation: it is used more frequently in a manner that is not thought to require explanation. The word riippuvuus (the closest equivalent to addiction in Finnish) was adopted more commonly in the reporting at the same time, in the 1990s. Thirdly, the results highlight individual self-governance as a superordinate principle in contemporary descriptions of addiction. If the principal demarcation in earlier texts was between us and them , it is now focused primarily on the individual s competence and ability to govern the self, to restrain and master one's behaviour. Finally, in the fourth study investigating textual constructions of female celebrities (Amy Winehouse, Britney Spears and Kate Moss) in Internet tabloids, various relations and functions of addiction problems, intoxication, body and gender were observed to function as cultural symbols. Addiction becomes a sign, or a style, that represents different significations in relation to the main characters in the tabloid stories. Tabloids, as a genre, play an important role by introducing other images of the problems than those featured in mainstream media. The study is positioned within the framework of modernity theory and its views on the need for self-reflexivity and biographies as tools for the creation and definition of the self. Traditional institutions such as the church, occupation, family etc. no longer play an important role in self-definition. This circumstance creates a need for a culture conveying stories of success and failure in relation to which the individual can position their own behaviour and life content. I propose that addiction , as a theme in media reporting, resolves the conflict that emanates from the ambivalence between the accessibility and the individualisation of consumer society, on the one hand, and the problematic behavioural patterns (addictions) that they may induce, on the other.

New Method for Delexicalization and its Application to Prosodic Tagging for Text-to-Speech Synthesis

This paper describes a new flexible delexicalization method based on glottal excited parametric speech synthesis scheme. The system utilizes inverse filtered glottal flow and all-pole modelling of the vocal tract. The method provides a possibil- ity to retain and manipulate all relevant prosodic features of any kind of speech. Most importantly, the features include voice quality, which has not been properly modeled in earlier delex- icalization methods. The functionality of the new method was tested in a prosodic tagging experiment aimed at providing word prominence data for a text-to-speech synthesis system. The ex- periment confirmed the usefulness of the method and further corroborated earlier evidence that linguistic factors influence the perception of prosodic prominence.

Dynamic programming based optimum non-uniform samples for speech reconstruction and coding

Non-uniform sampling of a signal is formulated as an optimization problem which minimizes the reconstruction signal error. Dynamic programming (DP) has been used to solve this problem efficiently for a finite duration signal. Further, the optimum samples are quantized to realize a speech coder. The quantizer and the DP based optimum search for non-uniform samples (DP-NUS) can be combined in a closed-loop manner, which provides distinct advantage over the open-loop formulation. The DP-NUS formulation provides a useful control over the trade-off between bitrate and performance (reconstruction error). It is shown that 5-10 dB SNR improvement is possible using DP-NUS compared to extrema sampling approach. In addition, the close-loop DP-NUS gives a 4-5 dB improvement in reconstruction error.

Simulating and Forecasting the Demand for New Consumer Durables

A diffusion/replacement model for new consumer durables designed to be used as a long-term forecasting tool is developed. The model simulates new demand as well as replacement demand over time. The model is called DEMSIM and is built upon a counteractive adoption model specifying the basic forces affecting the adoption behaviour of individual consumers. These forces are the promoting forces and the resisting forces. The promoting forces are further divided into internal and external influences. These influences are operationalized within a multi-segmental diffusion model generating the adoption behaviour of the consumers in each segment as an expected value. This diffusion model is combined with a replacement model built upon the same segmental structure as the diffusion model. This model generates, in turn, the expected replacement behaviour in each segment. To be able to use DEMSIM as a forecasting tool in early stages of a diffusion process estimates of the model parameters are needed as soon as possible after product launch. However, traditional statistical techniques are not very helpful in estimating such parameters in early stages of a diffusion process. To enable early parameter calibration an optimization algorithm is developed by which the main parameters of the diffusion model can be estimated on the basis of very few sales observations. The optimization is carried out in iterative simulation runs. Empirical validations using the optimization algorithm reveal that the diffusion model performs well in early long-term sales forecasts, especially as it comes to the timing of future sales peaks.

Multi-Pattern Viterbi Algorithm for joint decoding of multiple speech patterns

Joint decoding of multiple speech patterns so as to improve speech recognition performance is important, especially in the presence of noise. In this paper, we propose a Multi-Pattern Viterbi algorithm (MPVA) to jointly decode and recognize multiple speech patterns for automatic speech recognition (ASR). The MPVA is a generalization of the Viterbi Algorithm to jointly decode multiple patterns given a Hidden Markov Model (HMM). Unlike the previously proposed two stage Constrained Multi-Pattern Viterbi Algorithm (CMPVA),the MPVA is a single stage algorithm. MPVA has the advantage that it cart be extended to connected word recognition (CWR) and continuous speech recognition (CSR) problems. MPVA is shown to provide better speech recognition performance than the earlier techniques: using only two repetitions of noisy speech patterns (-5 dB SNR, 10% burst noise), the word error rate using MPVA decreased by 28.5%, when compared to using individual decoding. (C) 2010 Elsevier B.V. All rights reserved.

A Compact Model incorporating Quantum Effects for Ultra-Thin-Body Double-Gate MOSFETs

We propose a compact model which predicts the channel charge density and the drain current which match quite closely with the numerical solution obtained from the Full-Band structure approach. We show that, with this compact model, the channel charge density can be predicted by taking the capacitance based on the physical oxide thickness, as opposed to C-eff, which needs to be taken when using the classical solution.

Subspace Based Speech Enhancement Using Gaussian Mixture Model

Traditional subspace based speech enhancement (SSE)methods use linear minimum mean square error (LMMSE) estimation that is optimal if the Karhunen Loeve transform (KLT) coefficients of speech and noise are Gaussian distributed. In this paper, we investigate the use of Gaussian mixture (GM) density for modeling the non-Gaussian statistics of the clean speech KLT coefficients. Using Gaussian mixture model (GMM), the optimum minimum mean square error (MMSE) estimator is found to be nonlinear and the traditional LMMSE estimator is shown to be a special case. Experimental results show that the proposed method provides better enhancement performance than the traditional subspace based methods.Index Terms: Subspace based speech enhancement, Gaussian mixture density, MMSE estimation.

Two stage iterative wiener filtering for speech enhancement

We formulate a two-stage Iterative Wiener filtering (IWF) approach to speech enhancement, bettering the performance of constrained IWF, reported in literature. The codebook constrained IWF (CCIWF) has been shown to be effective in achieving convergence of IWF in the presence of both stationary and non-stationary noise. To this, we include a second stage of unconstrained IWF and show that the speech enhancement performance can be improved in terms of average segmental SNR (SSNR), Itakura-Saito (IS) distance and Linear Prediction Coefficients (LPC) parameter coincidence. We also explore the tradeoff between the number of CCIWF iterations and the second stage IWF iterations.

Comparison of AM-FM Based Features For Robust Speech Recognition

Effective feature extraction for robust speech recognition is a widely addressed topic and currently there is much effort to invoke non-stationary signal models instead of quasi-stationary signal models leading to standard features such as LPC or MFCC. Joint amplitude modulation and frequency modulation (AM-FM) is a classical non-parametric approach to non-stationary signal modeling and recently new feature sets for automatic speech recognition (ASR) have been derived based on a multi-band AM-FM representation of the signal. We consider several of these representations and compare their performances for robust speech recognition in noise, using the AURORA-2 database. We show that FEPSTRUM representation proposed is more effective than others. We also propose an improvement to FEPSTRUM based on the Teager energy operator (TEO) and show that it can selectively outperform even FEPSTRUM