933 resultados para Mason, David, 1726-1794.


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In the Court of general sessions for the city and county of Philadelphia. Habeas corpus for the custody of Frederick Sears Grand d'Hauteville.

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Mode of access: Internet.

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Vol. [7], "Life": 2nd ed., 1846. Vol. 5 in two parts, bound in two volumes.

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Competency in language and literacy are central to contemporary debates about education in Anglophone nations around the world. This paper suggests that such debates are informing not just educational policy but children’s literature itself as can be seen in Almond and McKean’s The Savage. This hybrid text combines prose and graphic narrative and narration in order to tell the story of Blue, a young British boy negotiating his identity in the aftermath of his father's death. While foregrounding a narrative of ideal masculinity, The Savage enacts and privileges a formal and thematic ideal of literacy as index of individual agency and development. Almond and McKean produce a politicised understanding of language and literacy that simultaneously positions The Savage in a textual tradition of socio-culturally disenfranchised youth, and intervenes in that tradition to (perhaps ironically) affirm the very conditions previously critiqued by that very tradition. Where earlier authors such as Barry Hines sought to challenge normative accounts of language and literacy in order to indict educational policy and praxes, Almond and McKean work to naturalise the very logics of education and agency by which their protagonist has been disenfranchised. In doing so, The Savage exemplifies current approaches to education which claim to value social and cultural diversity while imposing national standardised testing predicated on assumptions about the legitimacy of uniform standards and definitions of literacy.

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Traditional speech enhancement methods optimise signal-level criteria such as signal-to-noise ratio, but these approaches are sub-optimal for noise-robust speech recognition. Likelihood-maximising (LIMA) frameworks are an alternative that optimise parameters of enhancement algorithms based on state sequences generated for utterances with known transcriptions. Previous reports of LIMA frameworks have shown significant promise for improving speech recognition accuracies under additive background noise for a range of speech enhancement techniques. In this paper we discuss the drawbacks of the LIMA approach when multiple layers of acoustic mismatch are present – namely background noise and speaker accent. Experimentation using LIMA-based Mel-filterbank noise subtraction on American and Australian English in-car speech databases supports this discussion, demonstrating that inferior speech recognition performance occurs when a second layer of mismatch is seen during evaluation.

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Traditional speech enhancement methods optimise signal-level criteria such as signal-to-noise ratio, but such approaches are sub-optimal for noise-robust speech recognition. Likelihood-maximising (LIMA) frameworks on the other hand, optimise the parameters of speech enhancement algorithms based on state sequences generated by a speech recogniser for utterances of known transcriptions. Previous applications of LIMA frameworks have generated a set of global enhancement parameters for all model states without taking in account the distribution of model occurrence, making optimisation susceptible to favouring frequently occurring models, in particular silence. In this paper, we demonstrate the existence of highly disproportionate phonetic distributions on two corpora with distinct speech tasks, and propose to normalise the influence of each phone based on a priori occurrence probabilities. Likelihood analysis and speech recognition experiments verify this approach for improving ASR performance in noisy environments.

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The QUT-NOISE-TIMIT corpus consists of 600 hours of noisy speech sequences designed to enable a thorough evaluation of voice activity detection (VAD) algorithms across a wide variety of common background noise scenarios. In order to construct the final mixed-speech database, a collection of over 10 hours of background noise was conducted across 10 unique locations covering 5 common noise scenarios, to create the QUT-NOISE corpus. This background noise corpus was then mixed with speech events chosen from the TIMIT clean speech corpus over a wide variety of noise lengths, signal-to-noise ratios (SNRs) and active speech proportions to form the mixed-speech QUT-NOISE-TIMIT corpus. The evaluation of five baseline VAD systems on the QUT-NOISE-TIMIT corpus is conducted to validate the data and show that the variety of noise available will allow for better evaluation of VAD systems than existing approaches in the literature.

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Teaching The Global Dimension (2007) is intended for primary and secondary teachers, pre-service teachers and educators interested in fostering global concerns in the education system. It aims at linking theory and practice and is structured as follows. Part 1, the global dimension, proposes an educational framework for understanding global concerns. Individual chapters in this section deal with some educational responses to global issues and the ways in which young people might become, in Hick’s terms, more “world-minded”. In the first two chapters, Hicks presents first, some educational responses to global issues that have emerged in recent decades, and second, an outline of the evolution of global education as a specific field. As with all the chapters in this book, most of the examples are drawn from the United Kingdom. Young people’s concerns, student teachers’ views and the teaching of controversial issues, comprise the other chapters in this section. Taken collectively, the chapters in Part 2 articulate the conceptual framework for developing, teaching and evaluating a global dimension across the curriculum. Individual chapters in this section, written by a range of authors, explore eight key concepts considered necessary to underpin appropriate learning experiences in the classroom. These are conflict, social justice, values and perceptions, sustainability, interdependence, human rights, diversity and citizenship. These chapters are engaging and well structured. Their common format consists of a succinct introduction, reference to positive action for change, and examples of recent effective classroom practice. Two chapters comprise the final section of this book and suggest different ways in which the global dimension can be achieved in the primary and the secondary classroom.

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David Held is the Graham Wallace Chair in Political Science, and co-director of LSE Global Governance, at the London School of Economics. He is the author of many works, such as Cosmopolitanism: Ideals and Realities (2010); The Cosmopolitanism Reader (2010), with Garrett Brown; Globalisation/AntiGlobalisation (2007), Models of Democracy (2006), Global Covenant (2004) and Global Transformations: Politics, Economics and Culture (1999). Professor Held is also the co-founder, alongside Lord Professor Anthony Giddens, of Polity Press. Professor Held is widely known for his work concerning cosmopolitan theory, democracy, and social, political and economic global improvement. His Global Policy Journal endeavours to marry academic developments with practitioner realities, and contributes to the understanding and improvement of our governing systems.

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Robust speaker verification on short utterances remains a key consideration when deploying automatic speaker recognition, as many real world applications often have access to only limited duration speech data. This paper explores how the recent technologies focused around total variability modeling behave when training and testing utterance lengths are reduced. Results are presented which provide a comparison of Joint Factor Analysis (JFA) and i-vector based systems including various compensation techniques; Within-Class Covariance Normalization (WCCN), LDA, Scatter Difference Nuisance Attribute Projection (SDNAP) and Gaussian Probabilistic Linear Discriminant Analysis (GPLDA). Speaker verification performance for utterances with as little as 2 sec of data taken from the NIST Speaker Recognition Evaluations are presented to provide a clearer picture of the current performance characteristics of these techniques in short utterance conditions.