About: Training of Speaker-Clustered Acoustic Models for Use in Real-Time Recognizers     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
Description
  • The paper deals with training of speaker-clustered acoustic models. Various training techniques - Maximum Likelihood, Discriminative Training and two adaptation based on the MAP and Discriminative MAP were tested in order to minimize an impact of speaker changes to the correct function of the recognizer when a response of the automatic cluster detector is delayed or incorrect. Such situation is very frequent e.g. in on-line subtitling of TV discussions (Parliament meetings). In our experiments the best cluster-dependent training procedure was discriminative adaptation which provided the best trade-off between recognition results with correct and non-correct cluster detector information.
  • The paper deals with training of speaker-clustered acoustic models. Various training techniques - Maximum Likelihood, Discriminative Training and two adaptation based on the MAP and Discriminative MAP were tested in order to minimize an impact of speaker changes to the correct function of the recognizer when a response of the automatic cluster detector is delayed or incorrect. Such situation is very frequent e.g. in on-line subtitling of TV discussions (Parliament meetings). In our experiments the best cluster-dependent training procedure was discriminative adaptation which provided the best trade-off between recognition results with correct and non-correct cluster detector information. (en)
Title
  • Training of Speaker-Clustered Acoustic Models for Use in Real-Time Recognizers
  • Training of Speaker-Clustered Acoustic Models for Use in Real-Time Recognizers (en)
skos:prefLabel
  • Training of Speaker-Clustered Acoustic Models for Use in Real-Time Recognizers
  • Training of Speaker-Clustered Acoustic Models for Use in Real-Time Recognizers (en)
skos:notation
  • RIV/49777513:23520/09:00501736!RIV10-MSM-23520___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(2C06020)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 346660
http://linked.open...ai/riv/idVysledku
  • RIV/49777513:23520/09:00501736
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Acoustic models training; discriminative training; clustering; gender-dependent models (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [6DEB62423155]
http://linked.open...v/mistoKonaniAkce
  • Miláno
http://linked.open...i/riv/mistoVydani
  • Setúbal
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the International Conference on Signal Processing and Multimedia Application
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Pražák, Aleš
  • Psutka, Josef
  • Vaněk, Jan
  • Zelinka, Jan
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • INSTICC
https://schema.org/isbn
  • 978-989-674-007-8
http://localhost/t...ganizacniJednotka
  • 23520
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 77 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software