Voice recognition technologies appeared in the period of general device miniaturization, when all technologies were commonly integrated into one lust. There is no space for buttons and displays anymore.
To have a good system of Lithuanian language recognition, a number of throughout researches must be implemented. Only after selecting the most efficient speech recognition scheme, we can proceed to the development of software adapted to the contemporary time. The aim of this paper is to determine, how efficient speech recognition is possible using neuron networks. MFCC and LPC coefficients were chosen as the parameters characterizing the phonemes. The paper attempts at the determination of the coefficients, which lead to the most efficient recognition of phonemes. For testing, programs PRAAT and MatLab were used.
After implementing a number of phoneme recognition experiments in the research work, the results were obtained, which lead to the following conclusions:
1. In case of using neuron network for the recognition of isolated sounds and characterizing the phonemes by MFCC or LPC coefficients, the possibility of recognition does not exceed 90 per cent. It is not enough for quality recognition of Lithuanian speech.
2. In case of using MFCC coefficients, separate phonemes are recognized better than using LPC coefficients. The difference is about 15 per cent.
3. The advantage of LPC coefficients in comparison with MFCC is the curve of recognition possibility, which is more even... [to full text]
| Identifer | oai:union.ndltd.org:LABT_ETD/oai:elaba.lt:LT-eLABa-0001:E.02~2005~D_20050614_154005-58155 |
| Date | 14 June 2005 |
| Creators | Dobrovolskis, Martynas |
| Contributors | Lauruška, Vidas, Laurutis, Remigijus, Daunys, Gintautas, Laurutis, Vincas, Buinevičius, Vytautas Algimantas, Ščiukaitė, Janina, Siauliai University |
| Publisher | Lithuanian Academic Libraries Network (LABT), Siauliai University |
| Source Sets | Lithuanian ETD submission system |
| Language | Lithuanian |
| Detected Language | English |
| Type | Master thesis |
| Format | application/pdf |
| Source | http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2005~D_20050614_154005-58155 |
| Rights | Unrestricted |
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