45,951 research outputs found

    NPLDA: A Deep Neural PLDA Model for Speaker Verification

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    The state-of-art approach for speaker verification consists of a neural network based embedding extractor along with a backend generative model such as the Probabilistic Linear Discriminant Analysis (PLDA). In this work, we propose a neural network approach for backend modeling in speaker recognition. The likelihood ratio score of the generative PLDA model is posed as a discriminative similarity function and the learnable parameters of the score function are optimized using a verification cost. The proposed model, termed as neural PLDA (NPLDA), is initialized using the generative PLDA model parameters. The loss function for the NPLDA model is an approximation of the minimum detection cost function (DCF). The speaker recognition experiments using the NPLDA model are performed on the speaker verificiation task in the VOiCES datasets as well as the SITW challenge dataset. In these experiments, the NPLDA model optimized using the proposed loss function improves significantly over the state-of-art PLDA based speaker verification system.Comment: Published in Odyssey 2020, the Speaker and Language Recognition Workshop (VOiCES Special Session). Link to GitHub Implementation: https://github.com/iiscleap/NeuralPlda. arXiv admin note: substantial text overlap with arXiv:2001.0703

    Jefferson Digital Commons quarterly report: October-December 2019

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    This quarterly report includes: Articles Dean\u27s Research Development Lunch Conference Dissertations Educational Materials From the Archives Grand Rounds and Lectures Journals and Newsletters Population Health Presentation Materials Posters Reports Symposiums What People are Saying About the Jefferson Digital Common

    A Community-Based Participatory Action Research for Roma Health Justice in a Deprived District in Spain

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    Addressing health disparities and promoting health equity for Roma has been a challenge. The Roma are the largest disadvantaged ethnic minority population in Europe and have been the victims of deep social and economic injustices, institutional discrimination, and structural antigypsyism over many centuries. This has resulted in a much worse health status than their non-Roma counterparts. Current strategies based on ameliorative and top-down approaches to service delivery have resulted in paradoxical e_ects that solidify health disparities, since they do not e_ectively address the problems of vulnerable Roma groups. Following a health justice approach, we present a community-based participatory action research case study generated by a community and university partnership intended to address power imbalances and build collaboration among local stakeholders. This case study involved a group of health providers, Roma residents, researchers, Roma community organizations, and other stakeholders in the Poligono Sur, a neighborhood of Seville, Spain. The case study comprises four phases: (1) identifying Roma health assets, (2) empowering Roma community through sociopolitical awareness, (3) promoting alliances between Roma and community resources/institutions, and (4) building a common agenda for promoting Roma health justice. We highlighted best practices for developing processes to influence Roma health equity in local health policy agendas
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