This work focuses on speech recognition by computer, pattern recognition stages and problems. Also there is a goal to create a speech recognition tool. At the beginning, there is a general overview of the audio signal and language concepts. The subsequent presentation of the essential tasks of speech recognition, introduction to matrix algebra, which is used to described algorithm. Information is provided on what basis and how features are extracted. For this work often is used LPC. This algorithm is one of the most popular extracting features of speech signal, so it is reviewed in this paper, as well as its modification WLPC. The following text of the speech recognition gives theory of extracted features use. Section „Acoustic modeling“ describes the recognition of speech units and one of the most commonly used acoustic modeling technologies – Hidden Markov Models and the next section „Speech modeling“ describes the language modeling, which purpose is to correct data referring to dictionaries and speech structure. The rest of the text is focused on speach recognition using specrtogram and implementation of speach recognition system. After that, there were executed experiments, that where used to define quality of speech recognition. / Šiame darbe gilinamasi i kalbos atpažinima kompiuteriu, atpažinimo etapus, problemas, o veliau meginama sukurti kalbos atpažinimo iranki. Pradžioje, bendrai apžvelgiama garso signalo, kalbos savokos. Veliau pateikiamos kalbos atpažinimo esminiai uždaviniai, supažindinama su matricu algebra, kuri naudojama aprašytuose algoritmuose. Pateikiama informacija kuo remiantis ir kaip išskiriami požymiai. Šiam darbui dažnai naudojamas LPC. Šis algoritmas yra vienas iš populiariausiu išskiriant kalbos signalo požymius, todel jis šiame darbe yra apžvelgtas, kaip ir jo modifikacija WLPC. Toliau tekste pateikiama kalbos atpažinimo teorija, apie išskirtu požymiu panaudojima. Skyriuje „Akustinis modeliavimas“, aprašomas kalbos vienetu atpažinimas ir vienas iš dažniausiai naudojamu akustinio modeliavimo technologiju - pasleptieji Markov’o modeliai, sekantis skyrius „Kalbos modeliavimas“, aprašo kalbos modeliavima, skirta jau turimiems duomenims sutvarkyti, remiantis žodynais ir analizuojamos kalbos struktura. Likusioje teksto dalyje koncentruojamasi ties kalbos atpažinimu panaudojant spektrograma ir kalbos atpažinimo sistemos igyvendinimu. Po to atlikti eksperimentai, kuriais buvo tiriama pateikto algoritmo atpažinimo kokybe.
| Identifer | oai:union.ndltd.org:LABT_ETD/oai:elaba.lt:LT-eLABa-0001:E.02~2012~D_20140704_172117-57906 |
| Date | 04 July 2014 |
| Creators | Bardauskas, Justinas |
| Contributors | Bastys, Algirdas, Vilnius University |
| Publisher | Lithuanian Academic Libraries Network (LABT), Vilnius University |
| Source Sets | Lithuanian ETD submission system |
| Language | Lithuanian |
| Detected Language | Unknown |
| Type | Master thesis |
| Format | application/pdf |
| Source | http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2012~D_20140704_172117-57906 |
| Rights | Unrestricted |
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