Advanced Recognition of Lithuanian Digit Names Using Hybrid Approach

The paper deals with the recognition of digits and with the hybrid recognition technology. By the hybrid approach, we assume the combination of two or more different recognizers have to achieve higher recognition accuracy. Two Lithuanian recognizers using the word based and phoneme-based hidden Mark...

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Main Authors: Kastytis Ratkevicius, Gintare Paskauskaite, Gintare Bartisiute
Format: Article
Language:English
Published: Kaunas University of Technology 2018-04-01
Series:Elektronika ir Elektrotechnika
Subjects:
Online Access:http://eejournal.ktu.lt/index.php/elt/article/view/20638
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spelling doaj-5c654e2bf66647fd90c3fb0d778c8a922020-11-25T01:56:35ZengKaunas University of TechnologyElektronika ir Elektrotechnika1392-12152029-57312018-04-01242707310.5755/j01.eie.24.2.2063820638Advanced Recognition of Lithuanian Digit Names Using Hybrid ApproachKastytis RatkeviciusGintare PaskauskaiteGintare BartisiuteThe paper deals with the recognition of digits and with the hybrid recognition technology. By the hybrid approach, we assume the combination of two or more different recognizers have to achieve higher recognition accuracy. Two Lithuanian recognizers using the word based and phoneme-based hidden Markov models (HMM) together with the Spanish language recognizer 8.0 (Spanish-US) and Microsoft Speech Server Spanish language recognizer 9.0 (Spanish-US) were investigated. Using data mining package Weka, classification research was carried out with five different recognizer combining scenarios. The results of connecting two or three recognizers showed that the suggested method of using machine learning method to connect different recognizers greatly improved the recognition accuracy of digits speech corpus in all five cases. Manual annotation of the part of speech corpus enables to increase the recognition accuracy of Lithuanian digits names about 40 % using sub-word-based recognizer. SAMPA_LT set of phonemes is redundant for the digits recognition. DOI: http://dx.doi.org/10.5755/j01.eie.24.2.20638http://eejournal.ktu.lt/index.php/elt/article/view/20638classification algorithmshybrid intelligent systemsmachine learningspeech recognition.
collection DOAJ
language English
format Article
sources DOAJ
author Kastytis Ratkevicius
Gintare Paskauskaite
Gintare Bartisiute
spellingShingle Kastytis Ratkevicius
Gintare Paskauskaite
Gintare Bartisiute
Advanced Recognition of Lithuanian Digit Names Using Hybrid Approach
Elektronika ir Elektrotechnika
classification algorithms
hybrid intelligent systems
machine learning
speech recognition.
author_facet Kastytis Ratkevicius
Gintare Paskauskaite
Gintare Bartisiute
author_sort Kastytis Ratkevicius
title Advanced Recognition of Lithuanian Digit Names Using Hybrid Approach
title_short Advanced Recognition of Lithuanian Digit Names Using Hybrid Approach
title_full Advanced Recognition of Lithuanian Digit Names Using Hybrid Approach
title_fullStr Advanced Recognition of Lithuanian Digit Names Using Hybrid Approach
title_full_unstemmed Advanced Recognition of Lithuanian Digit Names Using Hybrid Approach
title_sort advanced recognition of lithuanian digit names using hybrid approach
publisher Kaunas University of Technology
series Elektronika ir Elektrotechnika
issn 1392-1215
2029-5731
publishDate 2018-04-01
description The paper deals with the recognition of digits and with the hybrid recognition technology. By the hybrid approach, we assume the combination of two or more different recognizers have to achieve higher recognition accuracy. Two Lithuanian recognizers using the word based and phoneme-based hidden Markov models (HMM) together with the Spanish language recognizer 8.0 (Spanish-US) and Microsoft Speech Server Spanish language recognizer 9.0 (Spanish-US) were investigated. Using data mining package Weka, classification research was carried out with five different recognizer combining scenarios. The results of connecting two or three recognizers showed that the suggested method of using machine learning method to connect different recognizers greatly improved the recognition accuracy of digits speech corpus in all five cases. Manual annotation of the part of speech corpus enables to increase the recognition accuracy of Lithuanian digits names about 40 % using sub-word-based recognizer. SAMPA_LT set of phonemes is redundant for the digits recognition. DOI: http://dx.doi.org/10.5755/j01.eie.24.2.20638
topic classification algorithms
hybrid intelligent systems
machine learning
speech recognition.
url http://eejournal.ktu.lt/index.php/elt/article/view/20638
work_keys_str_mv AT kastytisratkevicius advancedrecognitionoflithuaniandigitnamesusinghybridapproach
AT gintarepaskauskaite advancedrecognitionoflithuaniandigitnamesusinghybridapproach
AT gintarebartisiute advancedrecognitionoflithuaniandigitnamesusinghybridapproach
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