About: Region Dependent Linear Transforms in Multilingual Speech Recognition     Goto   Sponge   NotDistinct   Permalink

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Description
  • In today's speech recognition systems, linear or nonlinear transformations are usually applied to post-process speech features forming input to HMM based acoustic models. In this work, we experiment with three popular transforms: HLDA,MPE-HLDA and Region Dependent Linear Transforms (RDLT), which are trained jointly with the acoustic model to extract maximum of the discriminative information from the raw features and to represent it in a form suitable for the following GMM-HMM based acoustic model. We focus on multi-lingual environments, where limited resources are available for training recognizers of many languages. Using data from GlobalPhone database, we show that, under such restrictive conditions, the feature transformations can be advantageously shared across languages and robustly trained using data from several languages.
  • In today's speech recognition systems, linear or nonlinear transformations are usually applied to post-process speech features forming input to HMM based acoustic models. In this work, we experiment with three popular transforms: HLDA,MPE-HLDA and Region Dependent Linear Transforms (RDLT), which are trained jointly with the acoustic model to extract maximum of the discriminative information from the raw features and to represent it in a form suitable for the following GMM-HMM based acoustic model. We focus on multi-lingual environments, where limited resources are available for training recognizers of many languages. Using data from GlobalPhone database, we show that, under such restrictive conditions, the feature transformations can be advantageously shared across languages and robustly trained using data from several languages. (en)
Title
  • Region Dependent Linear Transforms in Multilingual Speech Recognition
  • Region Dependent Linear Transforms in Multilingual Speech Recognition (en)
skos:prefLabel
  • Region Dependent Linear Transforms in Multilingual Speech Recognition
  • Region Dependent Linear Transforms in Multilingual Speech Recognition (en)
skos:notation
  • RIV/00216305:26230/12:PU98188!RIV14-GA0-26230___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(FR-TI1/034), P(GPP202/12/P604), P(TA01011328), Z(MSM0021630528)
http://linked.open...vai/riv/dodaniDat
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  • 164601
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  • RIV/00216305:26230/12:PU98188
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http://linked.open.../riv/klicovaSlova
  • HLDA, Region Dependent Transforms, Minimum Phone Error, fMPE, multilingual speech recognition (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [1320E1C2F336]
http://linked.open...v/mistoKonaniAkce
  • Kyoto
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  • Kyoto
http://linked.open...i/riv/nazevZdroje
  • Proc. International Conference on Acoustics, Speech, and Signal Processing 2012
http://linked.open...in/vavai/riv/obor
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http://linked.open...iv/tvurceVysledku
  • Burget, Lukáš
  • Karafiát, Martin
  • Černocký, Jan
  • Janda, Miloš
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000312381404239
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://bibframe.org/vocab/doi
  • 10.1109/ICASSP.2012.6289014
http://purl.org/ne...btex#hasPublisher
  • IEEE Signal Processing Society
https://schema.org/isbn
  • 978-1-4673-0044-5
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  • 26230
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