Academic Journal

Algorithms of segmentation of speech signal on the correlated noise background

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Algorithms of segmentation of speech signal on the correlated noise background
Συγγραφείς: Omelchenko, Sergey
Πηγή: ScienceRise; № 4 (2018); 31-35
Στοιχεία εκδότη: OU Scientific Route, 2018.
Έτος έκδοσης: 2018
Θεματικοί όροι: УДК 621.391, speech segmentation, sliding-average autoregressive model, moment functions, formants, phonemes, correlated noise, сегментация речи, модель авторегрессии скользящего-среднего, моментные функции, форманти, фонемы, коррелированные помехи, 0211 other engineering and technologies, 02 engineering and technology, 0204 chemical engineering
Περιγραφή: Algorithms of segmentation based on formant and antiformant assessments are considered in the article. An algorithm for speech segmentation using momentary functions of third and fourth order is obtained. It is proposed to use digital filtering based on the sliding-average autoregressive model to suppress correlated noise. Estimates of variance in estimating the time boundaries of words for a number of proposed speech segmentation algorithms are obtained
Τύπος εγγράφου: Article
Other literature type
Περιγραφή αρχείου: application/pdf
ISSN: 2313-8416
2313-6286
DOI: 10.15587/2313-8416.2018.129703
Σύνδεσμος πρόσβασης: http://journals.uran.ua/sciencerise/article/download/129703/125423
http://journals.uran.ua/sciencerise/article/download/129703/125423
http://journals.uran.ua/sciencerise/article/view/129703
http://journals.uran.ua/sciencerise/article/view/129703
Rights: CC BY
Αριθμός Καταχώρησης: edsair.doi.dedup.....d96335152f72941db7af06b51018975b
Βάση Δεδομένων: OpenAIRE
Περιγραφή
ISSN:23138416
23136286
DOI:10.15587/2313-8416.2018.129703