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Statements

Subject Item
n2:RIV%2F49777513%3A23520%2F13%3A43921193%21RIV14-TA0-23520___
rdf:type
skos:Concept n4:Vysledek
rdfs:seeAlso
http://dx.doi.org/10.1007/978-3-642-40585-3_38
dcterms:description
The aim of this paper is to improve speech recognition by enriching language models with automatically detected foreign inclusions from a training text. The enriching is restricted only to foreign, proper-noun inclusions which are typically a dominant part of miss-recognized words. In our suggested approach, character-based n-gram language models are used for detection of foreign, single-word inclusions and for a language identification, and finite state transducers are used to generate foreign pronunciations. Results of this paper show that by enriching language model with English proper nouns found in Czech training text, the recognition of a speech containing English inclusions can be improved by 9.4% relative reduction of WER. The aim of this paper is to improve speech recognition by enriching language models with automatically detected foreign inclusions from a training text. The enriching is restricted only to foreign, proper-noun inclusions which are typically a dominant part of miss-recognized words. In our suggested approach, character-based n-gram language models are used for detection of foreign, single-word inclusions and for a language identification, and finite state transducers are used to generate foreign pronunciations. Results of this paper show that by enriching language model with English proper nouns found in Czech training text, the recognition of a speech containing English inclusions can be improved by 9.4% relative reduction of WER.
dcterms:title
Improving Speech Recognition by Detecting Foreign Inclusions and Generating Pronunciations Improving Speech Recognition by Detecting Foreign Inclusions and Generating Pronunciations
skos:prefLabel
Improving Speech Recognition by Detecting Foreign Inclusions and Generating Pronunciations Improving Speech Recognition by Detecting Foreign Inclusions and Generating Pronunciations
skos:notation
RIV/49777513:23520/13:43921193!RIV14-TA0-23520___
n4:predkladatel
n5:orjk%3A23520
n3:aktivita
n17:S n17:P
n3:aktivity
P(ED1.1.00/02.0090), P(TE01020197), S
n3:dodaniDat
n18:2014
n3:domaciTvurceVysledku
n7:1145177 n7:8780943
n3:druhVysledku
n11:D
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n22:predkladatel
n3:idSjednocenehoVysledku
79327
n3:idVysledku
RIV/49777513:23520/13:43921193
n3:jazykVysledku
n6:eng
n3:klicovaSlova
Language Identification, G2P, ASR
n3:klicoveSlovo
n12:G2P n12:ASR n12:Language%20Identification
n3:kontrolniKodProRIV
[7F1C53C550F0]
n3:mistoKonaniAkce
Plzeň
n3:mistoVydani
Berlin Heidelberg
n3:nazevZdroje
Text, Speech, and Dialogue 16th International Conference, TSD 2013, Pilsen, Czech Republic, September 1-5, 2013. Proceedings
n3:obor
n23:JD
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n21:ED1.1.00%2F02.0090 n21:TE01020197
n3:rokUplatneniVysledku
n18:2013
n3:tvurceVysledku
Švec, Jan Lehečka, Jan
n3:typAkce
n10:WRD
n3:zahajeniAkce
2013-09-01+02:00
s:issn
0302-9743
s:numberOfPages
8
n14:doi
10.1007/978-3-642-40585-3_38
n19:hasPublisher
Springer-Verlag
n8:isbn
978-3-642-40584-6
n13:organizacniJednotka
23520