Thesis Details
Dynamický dekodér pro rozpoznávání řeči
The result of this work is a fully working and significantly optimized implementation of a dynamic decoder. This decoder is based on dynamic recognition network generation and decoding by a modified version of the Token Passing algorithm. The implemented solution provides very similar results to the original static decoder from BSCORE (API of Phonexia company). Compared to BSCORE this implementation offers significant reduction of memory usage. This makes use of more complex language models possible. It also facilitates integration the speech recognition to some mobile devices or dynamic adding of new words to the system.
dynamic decoder, language model, acoustic model, speech recognition, recognition network, Token Passing algorithm, n-gram probabilities
Hrubý Martin, Ing., Ph.D. (DITS FIT BUT), člen
Janoušek Vladimír, doc. Ing., Ph.D. (DITS FIT BUT), člen
Jaroš Jiří, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Matyska Luděk, prof. RNDr., CSc. (FI MUNI), člen
Peringer Petr, Dr. Ing. (DITS FIT BUT), člen
@mastersthesis{FITMT20095, author = "Michal Vesel\'{y}", type = "Master's thesis", title = "Dynamick\'{y} dekod\'{e}r pro rozpozn\'{a}v\'{a}n\'{i} \v{r}e\v{c}i", school = "Brno University of Technology, Faculty of Information Technology", year = 2017, location = "Brno, CZ", language = "czech", url = "https://www.fit.vut.cz/study/thesis/20095/" }