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<p> There is little research available on Asian-Indians' attitudes toward seeking professional psychological help. Further, little research is available that addresses theoretical approaches that may be effective in reducing the stigma associated with psychological help in working with this underserved population. Therefore, this study provides a preliminary means to provide marriage and family therapy to Asian Indians. A repeated-measures research method was used to examine participants' attitudes toward seeking psychological help and compare those attitudes before and after a skills-based workshop on marital communication and conflict resolution. Workshops were held in Malaysia, India, and the United States. A total of 135 Asian Indian participants, who were all married, completed surveys before participation in the workshop and again immediately afterward. The influence of attitudes on marital satisfaction was examined as well as the relationship between conflict style and attitudes and marital satisfaction. Lastly, the study looked at the type of marriage--arranged and choice--and the relationships with attitudes and marital adjustment. Analyses of the data indicated that a skills-based workshop approach was linked to improved attitudes toward seeking professional psychological help. This study further examined the relationships between individual conflict styles and marital adjustment. Two conflict styles were found to have some association with marital adjustment. The results of this study have compelling implications for working with Asian Indians and other unique cultures that include an added dimension to multicultural counseling and education.</p>

In most of state-of-the-art speech recognition systems, Gaussian mixture models (GMMs) are used to model the density of the emitting states in the hidden Markov models (HMMs). In a conventional system, the model parameters of each GMM are estimated directly and independently given the alignment. This results a large number of model parameters to be estimated, and consequently, a large amount of training data is required to fit the model. In addition, different sources of acoustic variability that impact the accuracy of a recogniser such as pronunciation variation, accent, speaker factor and environmental noise are only weakly modelled and factorized by adaptation techniques such as maximum likelihood linear regression (MLLR), maximum a posteriori adaptation (MAP) and vocal tract length normalisation (VTLN). In this thesis, we will discuss an alternative acoustic modelling approach — the subspace Gaussian mixture model (SGMM), which is expected to deal with these two issues better. In an SGMM, the model parameters are derived from low-dimensional model and speaker subspaces that can capture phonetic and speaker correlations. Given these subspaces, only a small number of state-dependent parameters are required to derive the corresponding GMMs. Hence, the total number of model parameters can be reduced, which allows acoustic modelling with a limited amount of training data. In addition, the SGMM-based acoustic model factorizes the phonetic and speaker factors and within this framework, other source of acoustic variability may also be explored. In this thesis, we propose a regularised model estimation for SGMMs, which avoids overtraining in case that the training data is sparse. We will also take advantage of the structure of SGMMs to explore cross-lingual acoustic modelling for low-resource speech recognition. Here, the model subspace is estimated from out-domain data and ported to the target language system. In this case, only the state-dependent parameters need to be estimated which relaxes the requirement of the amount of training data. To improve the robustness of SGMMs against environmental noise, we propose to apply the joint uncertainty decoding (JUD) technique that is shown to be efficient and effective. We will report experimental results on the Wall Street Journal (WSJ) database and GlobalPhone corpora to evaluate the regularisation and cross-lingual modelling of SGMMs. Noise compensation using JUD for SGMM acoustic models is evaluated on the Aurora 4 database.

Socrates articulated it best, "Speak, so I may see you." Indeed, language represents an invisible probe into the mind. It is the medium through which we express our deepest thoughts, our aspirations, our views, our feelings, our inner reality. From the beginning of artificial intelligence, researchers have sought to impart human like understanding to machines. As much of our language represents a form of self expression, capturing thoughts, beliefs, evaluations, opinions, and emotions which are not available for scrutiny by an outside observer, in the field of natural language, research involving these aspects has crystallized under the name of subjectivity and sentiment analysis. While subjectivity classification labels text as either subjective or objective, sentiment classification further divides subjective text into either positive, negative or neutral. In this thesis, I investigate techniques of generating tools and resources for subjectivity analysis that do not rely on an existing natural language processing infrastructure in a given language. This constraint is motivated by the fact that the vast majority of human languages are scarce from an electronic point of view: they lack basic tools such as part-of-speech taggers, parsers, or basic resources such as electronic text, annotated corpora or lexica. This severely limits the implementation of techniques on par with those developed for English, and by applying methods that are lighter in the usage of text processing infrastructure, we are able to conduct multilingual subjectivity research in these languages as well. Since my aim is also to minimize the amount of manual work required to develop lexica or corpora in these languages, the techniques proposed employ a lever approach, where English often acts as the donor language (the fulcrum in a lever) and allows through a relatively minimal amount of effort to establish preliminary subjectivity research in a target language.

The composition of the United States population and its workforce is changing rapidly with a projected increase from 249 million in 1990 to 355 million by the year 2040. The majority white population is projected to only grow by 25 percent during this time period while the Latino, and Hispanic populations in the United States are projected to increase by 187 percent. Consequently, the current minorities will constitute more than half of the nation's total population by mid century and comprise a disproportionately large segment of the workforce. as a result of these changing demographics and increasing economic globalization, America's educational institutions will be confronted with reforming their curricula to meet new societal needs by promoting knowledge and understanding of different cultures.;The purpose of this study was to determine the levels of multicultural education integrated into the general education courses that are requirements for completion of AAS degree programs. Further, it was designed to identify the factors that influenced faculty members to include multicultural education into their courses.;Levels of integration of multicultural education were determined by personal interviews of faculty and supported by evidence presented in their syllabi, tests, and handouts. Analysis of the interviews provided the factors that motivate faculty members to infuse or not to infuse their classes with multicultural perspectives.;It was concluded that the amount of multicultural concepts infused into the courses vary from none to considerable and is determined by the faculty member's commitment to achieving pluralism. Factors that motivate inclusion are the disciplines, institutional atmosphere, and personal values of faculty.;Further study is needed to determine how much of the multicultural perspective students retain from the general education courses. A comparison between two and four-year colleges is needed to help determine whether only community college instructors are deficient in the amount of multicultural education they infuse into their disciplines.

Multicultural practitioners promote cultural competence among individuals to create awareness and tolerance of others who are culturally different. Yet, current research on cultural competence education primarily focused on practitioners in the traditional school setting instead of individuals in nonschool settings. This basic qualitative study investigated how multicultural practitioners in nonschool settings experience their attempts to develop cultural competence in constituents. Bennett's intercultural sensitivity, Koehn and Rosenau's multicultural competence, and Quappe and Cantatore's cultural awareness models informed the semi-structured interviews with 8 multicultural practitioners obtained via snowball sampling. Data were manually coded and analyzed to develop themes. Results indicated four ways participants conceptualized cultural competency, a five-part approach to cultural competence promotion, seven varying efforts to develop cultural competence, seven challenges that hindered their work, and four areas of success. Future studies might investigate differences in cultural competency efforts used by specific cultural groups and multicultural practitioners' growth as professionals to help to determine professional development programs that warrant implementation. This study will generate interest in developing cultural competence in groups and settings beyond the reach of traditional educational settings, thereby contributing to social change.

Simultaneous interpretation (SI) is a special kind of translation where the interpreter listens to a speaker, processes the spoken (or signed) source language message and produces an equivalent output in a target language, i.e., the interpreter produces one part of the message in the target language while simultaneously listening to the next part of the message in the source language. This thesis examines the process of simultaneous interpretation from an information processing point of view and describes the implications of such an approach for practical SI. Following an overview of research issues in SI literature, a definition of SI is given, pointing out the special characteristics of SI and the features that distinguish it from written translation and consecutive interpretation. A model incorporating various structural and functional components is then used to describe SI in terms of information processing. The focus of this investigation is on the integrative use of bottom-up and top-down processing mechanisms as typical features of human information processing systems. Subsequently the implications of the observations made about SI as an information process are considered within the context of practical SI. The various factors that influence the quality, speed and reliability of interpretation at all stages of the process are examined. Finally suggestions for the training of simultaneous interpreters are made. The thesis is concluded with the observation that SI is indeed a special kind of human information processing. Modelling SI in terms of information processing can contribute to the understanding of this complex process and its components. It is a powerful tool to enlighten the mechanisms and skills involved in SI and to establish efficient training programs for simultaneous interpreters.

Monumentality can be seen as a culmination of consensus. However, when consensus is not present, furthermore, when disagreements construct the dialog, the architecture that mediates this dialog becomes a monument itself. Walls, dividing territories and cities around the world, have become dreadful monuments within our collective imaginary. Imposed separation lines, they reinforce the differences between ethnic groups and become long-term markers of a failed dialogue. This thesis takes a spatialized model of disagreement, the university, and constructs a new urban typology able to mediate conflicted zones through notions of programmed monumentality. It challenges a border condition and actively erodes a hard line within a city by strategic insertions of "encounter-platforms" for the two communities. Nicosia, the capital of Cyprus has been scarred by historical events that have created a series of unique conditions throughout the city fabric. A swatch of land running from East to West and varying in width between 3 m and 18 m has been imposed to split the city in two ethnically uniform halves. This thesis proposes an International Erasmus University inside the Green Line breaking the four-decade-old stalemate between the two communities. With students acting as effective diplomats, the exchange of ideas and opinions will aim to dismantle the firmly established psychological division between the two communities. The project creates a series of urban and architectural interventions in the city in order to stitch the unproductive separation of the territory, by proposing a series of programmatic nodes in place of the original market street. The new typology reinvents the city center and implements new points of interaction while activating the decayed urban fabric around the Green Line. The demilitarized zone is then turned into a park for the city and the university which facilitates the ease of pedestrian traffic from the two originally divided cities.

Document clustering automatically organizes a document collection into distinct groups of similar documents on the basis of their contents. Most of existing document clustering techniques deal with monolingual documents (i.e., documents written in one language). However, with the trend of globalization and advances in Internet technology, an organization or individual often generates/acquires and subsequently archives documents in different languages, thus creating the need for multilingual document clustering (MLDC). Motivated by its significance and need, this study designs a translation-based MLDC technique. Our empirical evaluation results show that the proposed multilingual document clustering technique achieves satisfactory clustering effectiveness measured by both cluster recall and cluster precision.

<p>This exploratory qualitative study investigated the experiences of California community college undocumented students and their career development processes and issues. Twelve undocumented students from multiple backgrounds participated in semi-structured interviews. It was evident from the students' backgrounds that being undocumented was not just a Latino issue. Students identified career development barriers such as financial hardship, lack of support, and limitations in career related opportunities. Though these barriers were initially disruptive to the participants' career development, the same barriers eventually became an important part of the participants' identity as undocumented students. Making progress despite the barriers created learning experiences that enabled the students to garner support and ultimately forge forward. The idea of hope was a critical component of this process. While a faint sense of hope allowed participants to enter the community college, as they faced these barriers their sense of hope and resiliency was strengthened. An emerging theory of undocumented students' career development was presented as a result of the findings. </p>