SPEEch on the griD (SPEED). SPEEch on the griD (SPEED) Motivation Automatic speech processing computationally demanding in the training, optimalization.

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Presentation transcript:

SPEEch on the griD (SPEED)

SPEEch on the griD (SPEED) Motivation Automatic speech processing computationally demanding in the training, optimalization and testing phases, therefore optimalization is done „part by part“. But optimization of one part of the recognizer is not independent from the settings of the other parts, the optimalization process should be holistic, taking into account the influence of as much parameters as possible. Output Making power of GRID computing available to a wider community of researchers dealing with speech processing for everyday work Developing methods for holistic optimization and diagnostics in speech processing and tools implementing these methods in the grid platform Other to be added by the consortium

Tasks Establishment of contacts, investigation of the state of the art, formation of a consortium Methodology development for holistic optimization and holistic diagnostics ASR (may include speaker identification, speaker recognition and language recognition) Text to Speech (TTS) systems Implementation aspects - porting the computations in the automatic speech processing domain to the Grid platform –solving particular domain-dependent problems of using Grid computing in automatic speech processing Problem of needed high data transfers and its influence on Grid computing speed Data security and program security Storage possibilities for large speech and language databases in Grid, (including security and other aspects) Porting commercial applications to Grid The consortium is looking for partners with expertise in automatic speech processing, natural language processing, speech and language resources, speech and language modelling, optimalization, high-performance computing and preferably with own available computational capacity

SPEED, The holistic optimization The aim is to find clusters of the input parameters vector space that increase the system performance for the different training/testing tasks

Members NGIs: Slovakia: Milan Rusko (IISAS(Leader)) Speech processing group Ladislav Hluchy (IISAS (NIL)) Grid computing group Jozef Juhar (Tech. Univ. Košice) Speech processing Ireland: David O'Callaghan (Trinity College Dublin) Switzerland: Milos Cernak, Idiap research institute, Martigny UK: Martin Wynne (University of Oxford) John Coleman (Phonetics Laboratory at Oxford University) Claire Devereux (STFC) EGI.eu: Nuno Ferreira Gergely Sipos Karolis Eigelis We are looking for other partners