The subspace Gaussian mixture model-A structured model for speech recognition

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F11%3APU96096" target="_blank" >RIV/00216305:26230/11:PU96096 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

The subspace Gaussian mixture model-A structured model for speech recognition

Original language description

Speech recognition based on the Hidden Markov Model-Gaussian Mixture Model (HMM-GMM) framework generally involves training a completely separate GMM in each HMM state.We introduce a model in which the HMM states share a common structure but the means andmixture weights are allowed to vary in a subspace of the full parameter space, controlled by a global mapping from a vector space to the space of GMM parameters.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

JC - Computer hardware and software

OECD FORD branch

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Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2011

Confidentiality

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

Name of the periodical

COMPUTER SPEECH AND LANGUAGE

ISSN

0885-2308

e-ISSN

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Volume of the periodical

25

Issue of the periodical within the volume

2

Country of publishing house

GB - UNITED KINGDOM

Number of pages

36

Pages from-to

404-439

UT code for WoS article

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EID of the result in the Scopus database

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