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Lithuanian Speech Recognition Using Purely Phonetic Deep Learning

1
UAB Rubedo Sistemos, K. Baršausko g. 59, LT-51423 Kaunas, Lithuania
2
Institute of Mathematics, Silesian University of Technology, Kaszubska 23, 44-100 Gliwice, Poland
*
Author to whom correspondence should be addressed.
Computers 2019, 8(4), 76; https://doi.org/10.3390/computers8040076
Received: 1 October 2019 / Revised: 16 October 2019 / Accepted: 17 October 2019 / Published: 18 October 2019
Automatic speech recognition (ASR) has been one of the biggest and hardest challenges in the field. A large majority of research in this area focuses on widely spoken languages such as English. The problems of automatic Lithuanian speech recognition have attracted little attention so far. Due to complicated language structure and scarcity of data, models proposed for other languages such as English cannot be directly adopted for Lithuanian. In this paper we propose an ASR system for the Lithuanian language, which is based on deep learning methods and can identify spoken words purely from their phoneme sequences. Two encoder-decoder models are used to solve the ASR task: a traditional encoder-decoder model and a model with attention mechanism. The performance of these models is evaluated in isolated speech recognition task (with an accuracy of 0.993) and long phrase recognition task (with an accuracy of 0.992). View Full-Text
Keywords: Lithuanian speech recognition; phonetic encoder-decoder models; deep learning; artificial neural networks Lithuanian speech recognition; phonetic encoder-decoder models; deep learning; artificial neural networks
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Pipiras, L.; Maskeliūnas, R.; Damaševičius, R. Lithuanian Speech Recognition Using Purely Phonetic Deep Learning. Computers 2019, 8, 76.

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