"1"^^ . "ASR; Articulatory Features; spontaneous speech"@en . "[0281C9C31DEA]" . . "RIV/68407700:21230/14:00220036!RIV15-MSM-21230___" . "Mizera, Petr" . . . . "21230" . . "Estimation of Articulatory Features for Czech Language"@en . "RIV/68407700:21230/14:00220036" . . "2"^^ . . "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." . . "Estimation of Articulatory Features for Czech Language"@en . "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."@en . "Poll\u00E1k, Petr" . . . "Estimation of Articulatory Features for Czech Language" . "15050" . "Estimation of Articulatory Features for Czech Language" . "S" . . . . .