1. Influence of highly inflected word forms and acoustic background on the robustness of automatic speech recognition for human–computer interactionAndrej Žgank, 2022, original scientific article Abstract: Automatic speech recognition is essential for establishing natural communication with
a human–computer interface. Speech recognition accuracy strongly depends on the complexity of
language. Highly inflected word forms are a type of unit present in some languages. The acoustic
background presents an additional important degradation factor influencing speech recognition
accuracy. While the acoustic background has been studied extensively, the highly inflected word
forms and their combined influence still present a major research challenge. Thus, a novel type of
analysis is proposed, where a dedicated speech database comprised solely of highly inflected word
forms is constructed and used for tests. Dedicated test sets with various acoustic backgrounds were
generated and evaluated with the Slovenian UMB BN speech recognition system. The baseline word
accuracy of 93.88% and 98.53% was reduced to as low as 23.58% and 15.14% for the various acoustic
backgrounds. The analysis shows that the word accuracy degradation depends on and changes
with the acoustic background type and level. The highly inflected word forms’ test sets without
background decreased word accuracy from 93.3% to only 63.3% in the worst case. The impact of
highly inflected word forms on speech recognition accuracy was reduced with the increased levels of
acoustic background and was, in these cases, similar to the non-highly inflected test sets. The results
indicate that alternative methods in constructing speech databases, particularly for low-resourced
Slovenian language, could be beneficial.
Keywords: human–computer interaction, automatic speech recognition, acoustic modeling, highly inflected word forms, acoustic background
Published in DKUM: 28.03.2025; Views: 0; Downloads: 2
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2. Strategies for managing time and costs in speech corpus creation : insights from the Slovenian ARTUR corpusDarinka Verdonik, Andreja Bizjak, Andrej Žgank, Mirjam Sepesy Maučec, Mitja Trojar, Jerneja Žganec Gros, Marko Bajec, Iztok Lebar Bajec, Simon Dobrišek, 2024, original scientific article Abstract: Parliamentary debates represent an essential part of democratic discourse and provide insights into various socio-demographic and linguistic phenomena - parliamentary corpora, which contain transcripts of parliamentary debates and extensive metadata, are an important resource for parliamentary discourse analysis and other research areas. This paper presents the Slovenian parliamentary corpus siParl, the latest version of which contains transcripts of plenary sessions and other legislative bodies of the Assembly of the Republic of Slovenia from 1990 to 2022, comprising more than 1 million speeches and 210 million words. We outline the development history of the corpus and also mention other initiatives that have been influenced by siParl (such as the Parla-CLARIN encoding and the ParlaMint corpora of European parliaments), present the corpus creation process, ranging from the initial data collection to the structural development and encoding of the corpus, and given the growing influence of the ParlaMint corpora, compare siParl with the Slovenian ParlaMint-SI corpus. Finally, we discuss updates for the next version as well as the long-term development and enrichment of the siParl corpus.
Keywords: recording speech, transcribing speech, transcription guidelines, Less-resourced language
Published in DKUM: 04.02.2025; Views: 0; Downloads: 8
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4. Acoustic Gender and Age Classification as an Aid to Human–Computer Interaction in a Smart Home EnvironmentDamjan Vlaj, Andrej Žgank, 2023, original scientific article Abstract: The advanced smart home environment presents an important trend for the future of human wellbeing. One of the prerequisites for applying its rich functionality is the ability to differentiate between various user categories, such as gender, age, speakers, etc. We propose a model for an efficient acoustic gender and age classification system for human–computer interaction in a smart home. The objective was to improve acoustic classification without using high-complexity feature extraction. This was realized with pitch as an additional feature, combined with additional acoustic modeling approaches. In the first step, the classification is based on Gaussian mixture models. In thesecond step, two new procedures are introduced for gender and age classification. The first is based on the count of the frames with the speaker’s pitch values, and the second is based on the sum of the frames with pitch values belonging to a certain speaker. Since both procedures are based on pitch values, we have proposed a new, effective algorithm for pitch value calculation. In order to improve gender and age classification, we also incorporated speech segmentation with the proposed voice activity detection algorithm. We also propose a procedure that enables the quick adaptation of the classification algorithm to frequent smart home users. The proposed classification model with pitch values has improved the results in comparison with the baseline system.
Keywords: acoustic classification, acoustic signal processing, Gaussian mixture model, pitch analysis, smart home
Published in DKUM: 11.12.2023; Views: 471; Downloads: 23
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5. Načrtovanje govornega vmesnika : navodila za vajeAndrej Žgank, 2023, other educational material Keywords: telekomunikacije, govorni vmesniki, storitve, tonska izbira, avtomatsko razpoznavanje govora, avtomatska sinteza govora, navodila, vaje
Published in DKUM: 27.11.2023; Views: 425; Downloads: 19
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9. Govorni, dialoški in multimodalni jezikovni viri : pregled stanjaDarinka Verdonik, Andrej Žgank, Simona Majhenič, Izidor Mlakar, 2020, treatise, preliminary study, study Keywords: multimodalni jezikovni viri, jezikovni viri
Published in DKUM: 13.05.2020; Views: 1249; Downloads: 89
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10. Zaznavanje varnostnih groženj v komunikacijskih omrežjih in ukrepanje ob njihAljaž Gaber, 2020, master's thesis Abstract: V magistrskem delu smo se ukvarjali z ATP rešitvijo podjetja Trend Micro, DDI in DDA. Za izvedbo magistrskega dela smo podrobneje spoznali postopke uporabe DDI in DDA. Najprej smo opisali zmožnosti in funkcije DDI in DDA. Postavili smo ustrezni testni sistem in spremljali grožnje, ki se pojavljajo v komunikacijskih omrežjih, ter njihovo delovanje preučevali v peskovniku. Poleg tega smo primerjali vplive različnih vrst zlonamerne programske kode in analizirali postopke ukrepanj ob zaznanih varnostnih incidentih. V zadnjem delu naloge so predstavljeni predlogi za izboljšanje informacijske varnosti, ki smo jih definirali s pomočjo rezultatov obravnavanja groženj z DDI in DDA.
Keywords: informacijska varnost, napredni pristopi varovanja omrežja, informacijske grožnje, peskovnik
Published in DKUM: 24.02.2020; Views: 1322; Downloads: 242
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