Please join CUNY DHI for a special presentation of the NEH funded project HiPSTAS by Tanya Clement on March 5th, 2014 at the Graduate Center, CUNY. This event will take place in room C197 and is open to the public. This event will be livestreamed. Please register here.

http://www.eventbrite.com/e/tanya-clement-3514-630-830-hipstas-what-information-retrieval-machine-learning-and-visualizations-tickets-10742550257

“HiPSTAS, What?: Information Retrieval, Machine Learning, and Visualizations with Sound” Even digitized, unprocessed sound collections, which hold important cultural artifacts for the humanities such as poetry readings, story telling, speeches, oral histories, and other performances of the spoken word remain largely inaccessible.In order to increase access to recordings of significance to the humanities, Tanya Clement at the University of Texas School of Information in collaboration with David Tcheng and Loretta Auvil at the Illinois Informatics Institute at the University of Illinois, Urbana Champaign have developed the HiPSTAS (High Performance Sound Technologies for Access and Scholarship), which is currently being funded by an NEH Institute for Advanced Topics in the Digital Humanities grant and an NEH Preservation and Access Grant to develop and evaluate a computational system for archivists, librarians, and humanists for discovering and analyzing sound collections. The main premise behind HiPSTAS is that if we don’t use sound collections, we will not preserve. To this end, HiPSTAS has brought together humanists interested in sound scholarship, stewards of sound collections, and computer scientists and technologists versed in computational analytics and visualizations of sound to develop more productive tools for advancing scholarship in spoken text audio. This talk will introduce the project, the participants, and the processes and share early results.

Details here: http://cunydhi.commons.gc.cuny.edu/2014/02/26/tanya-clement-3514-630-830-hipstas-what-information-retrieval-machine-learning-and-visualizations-with-sound/

Please join CUNY DHI for a special presentation of the NEH funded project HiPSTAS by Tanya Clement on March 5th, 2014 at the Graduate Center, CUNY. This event will take place in room C197 and is open to the public. This event will be livestreamed. Please register here.

http://www.eventbrite.com/e/tanya-clement-3514-630-830-hipstas-what-information-retrieval-machine-learning-and-visualizations-tickets-10742550257

“HiPSTAS, What?: Information Retrieval, Machine Learning, and Visualizations with Sound” Even digitized, unprocessed sound collections, which hold important cultural artifacts for the humanities such as poetry readings, story telling, speeches, oral histories, and other performances of the spoken word remain largely inaccessible.In order to increase access to recordings of significance to the humanities, Tanya Clement at the University of Texas School of Information in collaboration with David Tcheng and Loretta Auvil at the Illinois Informatics Institute at the University of Illinois, Urbana Champaign have developed the HiPSTAS (High Performance Sound Technologies for Access and Scholarship), which is currently being funded by an NEH Institute for Advanced Topics in the Digital Humanities grant and an NEH Preservation and Access Grant to develop and evaluate a computational system for archivists, librarians, and humanists for discovering and analyzing sound collections. The main premise behind HiPSTAS is that if we don’t use sound collections, we will not preserve. To this end, HiPSTAS has brought together humanists interested in sound scholarship, stewards of sound collections, and computer scientists and technologists versed in computational analytics and visualizations of sound to develop more productive tools for advancing scholarship in spoken text audio. This talk will introduce the project, the participants, and the processes and share early results.

Details here: http://cunydhi.commons.gc.cuny.edu/2014/02/26/tanya-clement-3514-630-830-hipstas-what-information-retrieval-machine-learning-and-visualizations-with-sound/