. "Berlin" . "8"^^ . "Text, Speech, and Dialogue" . "RIV/68407700:21230/13:00207379!RIV14-MSM-21230___" . . . . . "978-3-642-40584-6" . "RIV/68407700:21230/13:00207379" . . "[64425D673B8F]" . "2"^^ . "S" . . "2013-09-01+02:00"^^ . . . "Han\u017El, V\u00E1clav" . "2"^^ . "0302-9743" . . . "Foot Detection in Czech Using Pitch Information and HMM" . . "Foot Detection in Czech Using Pitch Information and HMM"@en . . "21230" . "Barto\u0161ek, Jan" . . "In the presented work we are dealing with modelling and detection of lexical stress-group (foot) for Czech language. Detection of foot as one type of supra-segmental (prosody) information nearly corresponds to detection of word boundaries. Every native speaker is able to distinguish the feet in continuous speech, but on the other hand there are still no obvious connections between the sound qualities (pitch, intensity, syllable length) and foot prominence realization in Czech. In the experiment we tried to train the Hidden Markov Models (HMM) for Czech feet representation using only pitch information in the syllable nuclei. The most of Czech SPEECON database was used as an experiment source database. A necessary part of the presented system is a tool that transforms given Czech text into the foot units according to the known linguistic rules."@en . . "Springer-Verlag" . . . "Foot Detection in Czech Using Pitch Information and HMM" . . "Foot Detection in Czech Using Pitch Information and HMM"@en . . "75415" . "Plze\u0148" . "prosody; stressed-group detection; foot; pitch; clitics absorption; ASR; HMM"@en . . "In the presented work we are dealing with modelling and detection of lexical stress-group (foot) for Czech language. Detection of foot as one type of supra-segmental (prosody) information nearly corresponds to detection of word boundaries. Every native speaker is able to distinguish the feet in continuous speech, but on the other hand there are still no obvious connections between the sound qualities (pitch, intensity, syllable length) and foot prominence realization in Czech. In the experiment we tried to train the Hidden Markov Models (HMM) for Czech feet representation using only pitch information in the syllable nuclei. The most of Czech SPEECON database was used as an experiment source database. A necessary part of the presented system is a tool that transforms given Czech text into the foot units according to the known linguistic rules." . .