Computer Speech Recognition in Slovene Language

Matej Ulčar (2018) Computer Speech Recognition in Slovene Language. MSc thesis.

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Abstract

Manual transcription of speech is slow and is being replaced by automatic speech recognition systems. These systems are also used for voice control of various programs and devices. In this thesis, we used as a baseline for Slovene speech recognition GMM-HMM methods for acoustic model and n-grams for language model. We improved both models with deep neural networks, which have proven to be very successful. We tested several architectures of time-delayed neural networks and neural networks with long short-term memory for both acoustic and language model. We used a large lexicon, containing about a million words. Time-delayed neural networks achieved the best results on continuous speech, with 72,84% of correctly identified words.

Item Type:

Thesis (MSc thesis)

Keywords:

machine learning, deep neural networks, speech recognition

Number of Pages:

Language of Content:

Slovenian

Mentor / Comentors:

Name and Surname	ID	Function
prof. dr. Marko Robnik Šikonja	276	Mentor
izr. prof. dr. Simon Dobrišek		Comentor

Link to COBISS:

http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1538025411)

Institution:

University of Ljubljana

Department:

Faculty of Computer and Information Science

Item ID:

4283

Date Deposited:

08 Oct 2018 12:52

Last Modified:

14 Nov 2018 10:32

URI:

http://eprints.fri.uni-lj.si/id/eprint/4283

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