Kunkel's (1974) article on "Pomo kin groups" and Kronenfeld's response, in this issue (Kronenfeld 1975), bring to the fore once more the interesting problem of the ethnohistory of social structure. Kronenfeld is quite apt in his comparison with the Nuer whose residential groupings and seasonal movements do not exactly reflect the fact that the Nuer use the metaphor of unilineal kinship to describe and understand their own socio-political organization. Kunkel seems to have confused social organization for social structure and while he has much of the former type of data in hand the latter only seems to have existed in the minds of long deceased Pomo for it was not recorded by ethnographers or other reporters.

Neural networks, especially those with more than one hidden layer, have re-emerged in Automatic Speech Recognition (ASR) systems as replacements to emission models based on Gaussian Mixture Models (GMMs). While the use of these so-called Deep Neural Networks (DNNs) has enjoyed widespread success due to improvements in recognition results, the exact source of better recognition accuracy is not entirely understood. Using a bootstrap resampling framework that generates synthetic test set data satisfying conditional independence assumptions of the model while still using real observations, I show that DNNs used for both feature generation and hybrid acoustic modeling help compensate for incorrect conditional independence assumptions and help fix poor phone duration estimates of the hidden Markov Model (HMM).

Despite these improvements, the large increase in word error rates for DNN-HMM systems on real data compared to synthetic data suggests that one can improve recognition performance by modifying the training criterion. Since neural networks are log-linear at the output layer, I propose using sequences of last hidden layers as input to a log-linear model, and training that model with large-margin criteria. These Structured Support Vector Machine (SVM) approaches allow us to more directly minimize errors relevant to automatic speech recognition, and provide some guarantees on test set error. First, I show how one can generate better features by combining a neural network with a hidden Markov Support Vector Machine (HMSVM). Then, I propose a hybrid DNN-Structured SVM acoustic model and an online training algorithm that iteratively updates alignments for faster convergence. Training of this model falls under a class of approaches known as sequence-discriminative training, which are used to train state-of-the-art systems. This DNN-latent Structured SVM model beats alternative methods to sequence-discriminative training by 1.0% absolute, while needing 33-66% fewer utterances to converge.

Finally, I analyze the Structured SVM approach to sequence-discriminative training and compare it to standard methods. I show how the loss function for boosted Maximum Mutual Information is an upper bound of the hinge loss for the Structured SVM, and how such a relaxation precludes the use of aggressive boosting parameters needed for better results. Finally, I analyze four of the most popular sequence-discriminative training criteria – Maximum Mutual Information, boosted Maximum Mutual Information, Minimum Phone Error, and state-level Minimum Bayes Risk – and the latent Structured SVM using the bootstrap resampling framework, and compare how different sequence-discriminative training criteria compensate for data/model mismatch. Structured SVM models perform better for real rather than synthetic data, likely because the model makes fewer distributional assumptions about the underlying data.

Abstract

Today’s world, characterized by networked agencies, global flows, cultural hybridity, andmovements of people within and across borders, contextualizes tourism in many ways. Paying close attention to the multiple translations and circulations of the concept of “tourism” across the globe, this symposium endeavors to elaborate both the spatial and temporal dimensions of the conceptual history of tourism. With this theme in mind, the symposium will deal with the following questions: How has the western concept of tourism (primarily Anglophone and French) traveled to non-Western contexts in Asia (including the Middle East), Africa, or South America, thereby imposing a discursive hegemony of a conceptual lexicon? Which native/local concepts of hospitality have been displaced by this conceptual globalization or have transformedit? Do newly emerging forms of tourism across the globe contribute to the intellectual discussion of the “decline of the West” and the “provincialization of Europe,” or they are just furtherexamples of westernization?

 Keywords: Tourism; theory; concepts; world anthropologies

Through the case study of the Tsodilo World Heritage Site in Botswana, I investigate the relationship between heritage conservation and tourism development. This is done by analyzing what I argue are the opposing conservation aims of World Heritage status and the commodifying tendencies that this status encourages on cultural heritage through increased tourism. More specifically, "intangible heritage" (criterion vi of the World Heritage cultural listing criteria) is addressed as governments and NGOs in southern Africa are increasingly relying upon cultural heritage tourism to assist in the "development" of socially and economically marginalized populations. I discuss the transformation of local and national heritage sites into World Heritage sites through the processes of place making and heritage making, and I contend that heritage management plans for these sites do more than "manage," but rather accelerate cultural change and change in heritage values, especially for those sites designated for their intangible heritage.

In this dissertation, I also elaborate on issues of ethnicity and nationalism and women and development through an examination of the production of a heritage management plan at Tsodilo modeled on community-based natural resource management (CBNRM). Indeed, the significance of the tourism industry to Botswana's economy, coupled with the contentious relations that the government has with its ethnic minorities, foregrounds a critical examination of the politics of heritage and conservation in the country. Furthermore, due to Botswana's nationalist stance on identity politics as well as the globalizing processes of development, the gender roles of the country's ethnic minorities are being transformed as they progressively enter a market economy through their varied inductions into the tourism industry. As local communities living near Tsodilo are increasingly consigned to self-reliance through tourism development, I question whether commodification of the site's intangible heritage ultimately works against the conservation aims of World Heritage and, if so, in what specific ways. The case study of heritage and tourism at Tsodilo provides a window to looking at "development" in southern Africa, as well as how national narratives of inclusion and legitimacy produce a dilemma for the promotion of heritage tourism among Botswana's ethnic minorities.