228,806 research outputs found

    Bolder Together 2: Building Grassroots Movements for Change

    Get PDF
    California's demographics are changing fast, but rates of voting and civic participation haven't kept up. In four rapidly growing counties across the state, a group of funders is working with local organizations to support diverse communities to lift up their voice and exercise their power on issues that affect their rights and their quality of life. The work of the funders and their local partners is yielding important lessons as states and communities across the country begin to experience the dramatic demographic shifts that are transforming California. This new report documents key lessons for philanthropy from this work so far. The report is a follow-up to a 2011 report that told the story of the funders' early efforts. Now, after five years of grantmaking and intensive work in the four counties, California Civic Participation Funders tells a fuller story about how local organizations are coming together and working across issues to mobilize diverse communities to flex their democratic rights. The funders also reflect further on how philanthropy can work with local communities to create a nation where government acts in the interests of all of the people

    Analysis of a Modern Voice Morphing Approach using Gaussian Mixture Models for Laryngectomees

    Full text link
    This paper proposes a voice morphing system for people suffering from Laryngectomy, which is the surgical removal of all or part of the larynx or the voice box, particularly performed in cases of laryngeal cancer. A primitive method of achieving voice morphing is by extracting the source's vocal coefficients and then converting them into the target speaker's vocal parameters. In this paper, we deploy Gaussian Mixture Models (GMM) for mapping the coefficients from source to destination. However, the use of the traditional/conventional GMM-based mapping approach results in the problem of over-smoothening of the converted voice. Thus, we hereby propose a unique method to perform efficient voice morphing and conversion based on GMM,which overcomes the traditional-method effects of over-smoothening. It uses a technique of glottal waveform separation and prediction of excitations and hence the result shows that not only over-smoothening is eliminated but also the transformed vocal tract parameters match with the target. Moreover, the synthesized speech thus obtained is found to be of a sufficiently high quality. Thus, voice morphing based on a unique GMM approach has been proposed and also critically evaluated based on various subjective and objective evaluation parameters. Further, an application of voice morphing for Laryngectomees which deploys this unique approach has been recommended by this paper.Comment: 6 pages, 4 figures, 4 tables; International Journal of Computer Applications Volume 49, Number 21, July 201

    Our Voice Is Your Future: Giving L.A.'s Youth Real Voice and Real Power

    Get PDF
    Based on focus groups with youth and youth workers, identifies best practices and opportunities to engage youth in community-building. Includes recommendations to improve social services and prevention, support and development, and participation

    Simulating dysarthric speech for training data augmentation in clinical speech applications

    Full text link
    Training machine learning algorithms for speech applications requires large, labeled training data sets. This is problematic for clinical applications where obtaining such data is prohibitively expensive because of privacy concerns or lack of access. As a result, clinical speech applications are typically developed using small data sets with only tens of speakers. In this paper, we propose a method for simulating training data for clinical applications by transforming healthy speech to dysarthric speech using adversarial training. We evaluate the efficacy of our approach using both objective and subjective criteria. We present the transformed samples to five experienced speech-language pathologists (SLPs) and ask them to identify the samples as healthy or dysarthric. The results reveal that the SLPs identify the transformed speech as dysarthric 65% of the time. In a pilot classification experiment, we show that by using the simulated speech samples to balance an existing dataset, the classification accuracy improves by about 10% after data augmentation.Comment: Will appear in Proc. of ICASSP 201

    The Diamond Approach and Christian Ministry

    Get PDF

    Mechanical and durability performance of lightweight concrete brick with palm oil fuel ash (POFA)

    Get PDF
    Lightweight building materials such as precast roof and wall panel has been widely used in the construction industries. This is because lightweight materials could benefits the economy and society in terms of manufacturing, transportation and handling cost. One of the most preferable lightweight material is Expanded Polystyrene (EPS). EPS consist of 98% of air and 2% of polystyrene. Therefore, EPS is very low in density which could contribute in the reduction of building materials mass. Abundance of studies has shown that EPS has significantly contribute to the reduction of brick density. EPS has been used as the aggregates replacement in concrete. However, the existing of EPS in the concrete has reduce the strength performance of the concrete. Due to this, researchers have extend their research in improvising the EPS concrete and brick strength with the addition of pozzolanic materials such as fly ash, rice husk ask, silica fume and etc [1-4]. The ability of these pozzolanic materials in enhancing the strength of brick or concrete has been proven..

    Technology Target Studies: Technology Solutions to Make Patient Care Safer and More Efficient

    Get PDF
    Presents findings on technologies that could enhance care delivery, including patient records and medication processes; features and functionality nurses require, including tracking, interoperability, and hand-held capability; and best practices
    • …
    corecore