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Optimized Acoustic Likelihoods Computation for NVIDIA and ATI/AMD Graphics Processors

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F12%3A43921648" target="_blank" >RIV/49777513:23520/12:43921648 - isvavai.cz</a>

  • Result on the web

    <a href="http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6169951" target="_blank" >http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6169951</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/TASL.2012.2190928" target="_blank" >10.1109/TASL.2012.2190928</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Optimized Acoustic Likelihoods Computation for NVIDIA and ATI/AMD Graphics Processors

  • Original language description

    In this paper, we describe an optimized version of a Gaussian-mixture-based acoustic model likelihood evaluation algorithm for graphical processing units (GPUs). The evaluation of these likelihoods is one of the most computationally intensive parts of automatic speech recognizers, but it can be parallelized and offloaded to GPU devices. Our approach offers a significant speed-up over the recently published approaches, because it utilizes the GPU architecture in a more effective manner. All the recent implementations have been intended only for NVIDIA graphics processors, programmed either in CUDA or OpenCL GPU programming frameworks. We present results for both CUDA and OpenCL. Further, we have developed an OpenCL implementation optimized for ATI/AMD GPUs. Results suggest that even very large acoustic models can be used in real-time speech recognition engines on computers equipped with a low-end GPU or laptops. In addition, the completely asynchronous GPU management provides additional

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    JD - Use of computers, robotics and its application

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2012

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING

  • ISSN

    1558-7916

  • e-ISSN

  • Volume of the periodical

    20

  • Issue of the periodical within the volume

    6

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    11

  • Pages from-to

    1818-1828

  • UT code for WoS article

    000302742400001

  • EID of the result in the Scopus database