Automatic spoken language identification utilizing acoustic and phonetic speech information

Automatic spoken Language Identi¯cation (LID) is the process of identifying the language spoken within an utterance. The challenge that this task presents is that no prior information is available indicating the content of the utterance or the identity of the speaker. The trend of globalization and the pervasive popularity of the Internet will amplify the need for the capabilities spoken language identi¯ca- tion systems provide. A prominent application arises in call centers dealing with speakers speaking di®erent languages. Another important application is to index or search huge speech data archives and corpora that contain multiple languages. The aim of this research is to develop techniques targeted at producing a fast and more accurate automatic spoken LID system compared to the previous National Institute of Standards and Technology (NIST) Language Recognition Evaluation. Acoustic and phonetic speech information are targeted as the most suitable fea- tures for representing the characteristics of a language. To model the acoustic speech features a Gaussian Mixture Model based approach is employed. Pho- netic speech information is extracted using existing speech recognition technol- ogy. Various techniques to improve LID accuracy are also studied. One approach examined is the employment of Vocal Tract Length Normalization to reduce the speech variation caused by di®erent speakers. A linear data fusion technique is adopted to combine the various aspects of information extracted from speech. As a result of this research, a LID system was implemented and presented for evaluation in the 2003 Language Recognition Evaluation conducted by the NIST.

The role of social skills and school connectedness in preadolescent depressive symptoms

In the current study, we tested whether school connectedness mediates more distal deficits in social skills in influencing depressive symptoms in a sample of 127 sixth- and seventh-grade students. Results demonstrated that school connectedness and social skills accounted for 44% and 26% of variance in depressive symptoms respectively and 49% in a combined model. Although the full mediation model hypothesis was not supported, follow-up analyses revealed that school connectedness partially mediated the link between social skills and preadolescent depressive symptoms. Thus, school connectedness appears to play as strong a role in depressive symptoms in this younger preadolescent age group.

Whitening Race: Essays In Social And Cultural Criticism In Australia

Aileen Moreton-Robinson has brought together scholars from a range of disciplines: philosophy, cultural and gender studies, education, social work, sociology and literary studies. All engage critically with the location of the social and discursive construction of whiteness.

After the marketplace: evidence, social science and educational research

This paper is an essay on the state of Australian education that frames new directions for educational research. It outlines three challenges faced by Australian educators: highly spatialised poverty with particularly strong mediating effects on primary school education; the need for intellectual and critical depth in pedagogy, with a focus in the upper primary and middle years; and the need to reinvent senior schooling to address emergent pathways from school to work and civic life. It offers a narrative description of the dynamics of policy making in Australia and North America and argues for an evidence-based approach to social and educational policy – but one quite unlike current test and market-based approaches. Instead, it argues for a multidisciplinary approach to a broad range of empirical and case-based evidence that subjects these to critical, hermeneutic social sciences. Such an approach would join educational policy with educational research, and broader social, community and governmental action with the aim of reorganising and redistributing material, cultural and social resources.

Identification of acoustic emission wave modes for accurate source location in plate-like structures

Acoustic emission (AE) technique is a popular tool used for structural health monitoring of civil, mechanical and aerospace structures. It is a non-destructive method based on rapid release of energy within a material by crack initiation or growth in the form of stress waves. Recording of these waves by means of sensors and subsequent analysis of the recorded signals convey information about the nature of the source. Ability to locate the source of stress waves is an important advantage of AE technique; but as AE waves travel in various modes and may undergo mode conversions, understanding of the modes (‘modal analysis’) is often necessary in order to determine source location accurately. This paper presents results of experiments aimed at finding locations of artificial AE sources on a thin plate and identifying wave modes in the recorded signal waveforms. Different source locating techniques will be investigated and importance of wave mode identification will be explored.