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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F14%3A00220036%21RIV15-MSM-21230___
rdf:type
skos:Concept n14:Vysledek
dcterms:description
The issues of automatic speech recognition (ASR) aimed at the Czech language have been intensively studied in the past decades. The researches have successfully managed to develop several practical applications such as dictation programs, automatic broadcast transcription (subtitling) and others. Accuracy of these ASR systems is generally satisfactory high, however it is significantly lower if the signal is corrupted, e.g. in the case of high-level background noise, spontaneous speech or when speech is masked and pronounced in a reduced form. These issues are still an obstacle for a wider usage of voice recognition technology under such conditions, because commonly achieved WER (Word Error Rate) of spontaneous speech recognition is above 50% in average. A possible solution to overcome this deficiency can be in the usage of speech production knowledge within ASR systems. Consequently, the speech production knowledge based on articulatory features (AFs) starts being used more often at feature level with the main purpose of improving the recognition of spontaneous or casual speech. The aim of our research is to analyse the possible contribution of articulatory features to the description of spontaneous or casual speech aimed for the Czech language. The issues of automatic speech recognition (ASR) aimed at the Czech language have been intensively studied in the past decades. The researches have successfully managed to develop several practical applications such as dictation programs, automatic broadcast transcription (subtitling) and others. Accuracy of these ASR systems is generally satisfactory high, however it is significantly lower if the signal is corrupted, e.g. in the case of high-level background noise, spontaneous speech or when speech is masked and pronounced in a reduced form. These issues are still an obstacle for a wider usage of voice recognition technology under such conditions, because commonly achieved WER (Word Error Rate) of spontaneous speech recognition is above 50% in average. A possible solution to overcome this deficiency can be in the usage of speech production knowledge within ASR systems. Consequently, the speech production knowledge based on articulatory features (AFs) starts being used more often at feature level with the main purpose of improving the recognition of spontaneous or casual speech. The aim of our research is to analyse the possible contribution of articulatory features to the description of spontaneous or casual speech aimed for the Czech language.
dcterms:title
Estimation of Articulatory Features for Czech Language Estimation of Articulatory Features for Czech Language
skos:prefLabel
Estimation of Articulatory Features for Czech Language Estimation of Articulatory Features for Czech Language
skos:notation
RIV/68407700:21230/14:00220036!RIV15-MSM-21230___
n3:aktivita
n13:S
n3:aktivity
S
n3:dodaniDat
n6:2015
n3:domaciTvurceVysledku
n7:6738524
n3:druhVysledku
n16:O
n3:duvernostUdaju
n8:S
n3:entitaPredkladatele
n10:predkladatel
n3:idSjednocenehoVysledku
15050
n3:idVysledku
RIV/68407700:21230/14:00220036
n3:jazykVysledku
n15:eng
n3:klicovaSlova
ASR; Articulatory Features; spontaneous speech
n3:klicoveSlovo
n4:ASR n4:Articulatory%20Features n4:spontaneous%20speech
n3:kontrolniKodProRIV
[0281C9C31DEA]
n3:obor
n12:JA
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
2
n3:rokUplatneniVysledku
n6:2014
n3:tvurceVysledku
Mizera, Petr Pollák, Petr
n9:organizacniJednotka
21230