Re-thinking home economics : from modern to postmodern accounts of pedagogical bodies

Two perceptions of the marginality of home economics are widespread across educational and other contexts. One is that home economics and those who engage in its pedagogy are inevitably marginalised within patriarchal relations in education and culture. This is because home economics is characterised as women's knowledge, for the private domain of the home. The other perception is that only orthodox epistemological frameworks of inquiry should be used to interrogate this state of affairs. These perceptions have prompted leading theorists in the field to call for non-essentialist approaches to research in order to re-think the thinking that has produced this cul-de-sac positioning of home economics as a body of knowledge and a site of teacher practice. This thesis takes up the challenge of working to locate a space outside the frame of modernist research theory and methods, recognising that this shift in epistemology is necessary to unsettle the idea that home economics is inevitably marginalised. The purpose of the study is to reconfigure how we have come to think about home economics teachers and the profession of home economics as a site of cultural practice, in order to think it otherwise (Lather, 1991). This is done by exploring how the culture of home economics is being contested from within. To do so, the thesis uses a 'posthumanist' approach, which rejects the conception of the individual as a unitary and fixed entity, but instead as a subject in process, shaped by desires and language which are not necessarily consciously determined. This posthumanist project focuses attention on pedagogical body subjects as the 'unsaid' of home economics research. It works to transcend the modernist dualism of mind/body, and other binaries central to modernist work, including private/public, male/female,paid/unpaid, and valued/unvalued. In so doing, it refuses the simple margin/centre geometry so characteristic of current perceptions of home economics itself. Three studies make up this work. Studies one and two serve to document the disciplined body of home economics knowledge, the governance of which works towards normalisation of the 'proper' home economics teacher. The analysis of these accounts of home economics teachers by home economics teachers, reveals that home economics teachers are 'skilled' yet they 'suffer' for their profession. Further,home economics knowledge is seen to be complicit in reinforcing the traditional roles of masculinity and femininity, thereby reinforcing heterosexual normativity which is central to patriarchal society. The third study looks to four 'atypical'subjects who defy the category of 'proper' and 'normal' home economics teacher. These 'atypical' bodies are 'skilled' but fiercely reject the label of 'suffering'. The discussion of the studies is a feminist poststructural account, using Russo's (1994) notion of the grotesque body, which is emergent from Bakhtin's (1968) theory of the carnivalesque. It draws on the 'shreds' of home economics pedagogy,scrutinising them for their subversive, transformative potential. In this analysis, the giving and taking of pleasure and fun in the home economics classroom presents moments of surprise and of carnival. Foucault's notion of the construction of the ethical individual shows these 'atypical' bodies to be 'immoderate' yet striving hard to be 'continent' body subjects. This research captures moments of transgression which suggest that transformative moments are already embodied in the pedagogical practices of home economics teachers, and these can be 'seen' when re-looking through postmodemist lenses. Hence, the cultural practices ofhome economics as inevitably marginalised are being contested from within. Until now, home economics as a lived culture has failed to recognise possibilities for reconstructing its own field beyond the confines of modernity. This research is an example of how to think about home economics teachers and the profession as a reconfigured cultural practice. Future research about home economics as a body of knowledge and a site of teacher practice need not retell a simple story of oppression. Using postmodemist epistemologies is one way to provide opportunities for new ways of looking.

Acoustic keyword spotting in speech with applications to data mining

Keyword Spotting is the task of detecting keywords of interest within continu- ous speech. The applications of this technology range from call centre dialogue systems to covert speech surveillance devices. Keyword spotting is particularly well suited to data mining tasks such as real-time keyword monitoring and unre- stricted vocabulary audio document indexing. However, to date, many keyword spotting approaches have su®ered from poor detection rates, high false alarm rates, or slow execution times, thus reducing their commercial viability. This work investigates the application of keyword spotting to data mining tasks. The thesis makes a number of major contributions to the ¯eld of keyword spotting. The ¯rst major contribution is the development of a novel keyword veri¯cation method named Cohort Word Veri¯cation. This method combines high level lin- guistic information with cohort-based veri¯cation techniques to obtain dramatic improvements in veri¯cation performance, in particular for the problematic short duration target word class. The second major contribution is the development of a novel audio document indexing technique named Dynamic Match Lattice Spotting. This technique aug- ments lattice-based audio indexing principles with dynamic sequence matching techniques to provide robustness to erroneous lattice realisations. The resulting algorithm obtains signi¯cant improvement in detection rate over lattice-based audio document indexing while still maintaining extremely fast search speeds. The third major contribution is the study of multiple veri¯er fusion for the task of keyword veri¯cation. The reported experiments demonstrate that substantial improvements in veri¯cation performance can be obtained through the fusion of multiple keyword veri¯ers. The research focuses on combinations of speech background model based veri¯ers and cohort word veri¯ers. The ¯nal major contribution is a comprehensive study of the e®ects of limited training data for keyword spotting. This study is performed with consideration as to how these e®ects impact the immediate development and deployment of speech technologies for non-English languages.

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 use of phase in complex spectrum subtraction for robust speech recognition

In this paper we propose a new method for utilising phase information by complementing it with traditional magnitude-only spectral subtraction speech enhancement through Complex Spectrum Subtraction (CSS). The proposed approach has the following advantages over traditional magnitude-only spectral subtraction: (a) it introduces complementary information to the enhancement algorithm; (b) it reduces the total number of algorithmic parameters, and; (c) is designed for improving clean speech magnitude spectra and is therefore suitable for both automatic speech recognition (ASR) and speech perception applications. Oracle-based ASR experiments verify this approach, showing an average of 20% relative word accuracy improvements when accurate estimates of the phase spectrum are available. Based on sinusoidal analysis and assuming stationarity between observations (which is shown to be better approximated as the frame rate is increased), this paper also proposes a novel method for acquiring the phase information called Phase Estimation via Delay Projection (PEDEP). Further oracle ASR experiments validate the potential for the proposed PEDEP technique in ideal conditions. Realistic implementation of CSS with PEDEP shows performance comparable to state of the art spectral subtraction techniques in a range of 15-20 dB signal-to-noise ratio environments. These results clearly demonstrate the potential for using phase spectra in spectral subtractive enhancement applications, and at the same time highlight the need for deriving more accurate phase estimates in a wider range of noise conditions.

Microphone array beamforming approach to blind speech separation

In this paper, we present a microphone array beamforming approach to blind speech separation. Unlike previous beamforming approaches, our system does not require a-priori knowledge of the microphone placement and speaker location, making the system directly comparable other blind source separation methods which require no prior knowledge of recording conditions. Microphone location is automatically estimated using an assumed noise field model, and speaker locations are estimated using cross correlation based methods. The system is evaluated on the data provided for the PASCAL Speech Separation Challenge 2 (SSC2), achieving a word error rate of 58% on the evaluation set.

Low-cost hardware speech enhancement for improved speech recognition in automotive environments

Voice recognition is one of the key enablers to reduce driver distraction as in-vehicle systems become more and more complex. With the integration of voice recognition in vehicles, safety and usability are improved as the driver’s eyes and hands are not required to operate system controls. Whilst speaker independent voice recognition is well developed, performance in high noise environments (e.g. vehicles) is still limited. La Trobe University and Queensland University of Technology have developed a low-cost hardware-based speech enhancement system for automotive environments based on spectral subtraction and delay–sum beamforming techniques. The enhancement algorithms have been optimised using authentic Australian English collected under typical driving conditions. Performance tests conducted using speech data collected under variety of vehicle noise conditions demonstrate a word recognition rate improvement in the order of 10% or more under the noisiest conditions. Currently developed to a proof of concept stage there is potential for even greater performance improvement.

Informed learning: a pedagogical construct attending simultaneously to information use and learning.

The idea of informed learning, applicable in academic, workplace and community settings, has been derived largely from a program of phenomenographic research in the field of information literacy, which has illuminated the experience of using information to learn. Informed learning is about simultaneous attention to information use and learning, where both information and learning are considered to be relational; and is built upon a series of key concepts such as second–order perspective, simultaneity, awareness, and relationality. Informed learning also relies heavily on reflection as a strategy for bringing about learning. As a pedagogical construct, informed learning supports inclusive curriculum design and implementation. This paper reports aspects of the informed learning research agenda which are currently being pursued at the Queensland University of Technology (QUT). The first part elaborates the idea of informed learning, examines the key concepts underpinning this pedagogical construct, and explains its emergence from the research base of the QUT Information Studies research team. The second presents a case, which demonstrates the ongoing development of informed learning theory and practice, through the development of inclusive informed learning for a culturally diverse higher education context.

Copyrights and creative commons licensing : pedagogical innovation in a higher education media literacy classroom

This article examines the role of copyrights in contemporary media literacies. It argues that, provided they are ethical, young people’s engagement with text should occur in environments that are as free from restriction as possible. Discussion of open culture ecologies and the emergent education commons is followed by a theorisation of both literacy and copyrights education as forms of epistemology: that is, as effects of knowledge producing discourses and practices. Because Creative Commons licenses respect and are based on existing copyright laws, a brief overview of traditional copyrights for educators is first provided. We then describe the voluntary Creative Commons copyright licensing framework (“some rights reserved”) as an alternative to conventional “all rights reserved” models. This is followed by an account of a series of workshop activities on copyrights and Creative Commons conducted by the authors in the media literacy classes of a preservice teacher education program in Queensland, Australia. It provides one example of a practical program on critical copyrights approaches, which may be adapted and used by other school and higher education institutions.

Recognising audio-visual speech in vehicles using the AVICAR database

Interacting with technology within a vehicle environment using a voice interface can greatly reduce the effects of driver distraction. Most current approaches to this problem only utilise the audio signal, making them susceptible to acoustic noise. An obvious approach to circumvent this is to use the visual modality in addition. However, capturing, storing and distributing audio-visual data in a vehicle environment is very costly and difficult. One current dataset available for such research is the AVICAR [1] database. Unfortunately this database is largely unusable due to timing mismatch between the two streams and in addition, no protocol is available. We have overcome this problem by re-synchronising the streams on the phone-number portion of the dataset and established a protocol for further research. This paper presents the first audio-visual results on this dataset for speaker-independent speech recognition. We hope this will serve as a catalyst for future research in this area.