dr inż. Adam Kurowski
Zatrudnienie
- Adiunkt w Katedra Systemów Multimedialnych
- Specjalista informatyk w Katedra Systemów Multimedialnych
Kontakt dla biznesu
- Lokalizacja
- Al. Zwycięstwa 27, 80-219 Gdańsk
- Telefon
- +48 58 348 62 62
- biznes@pg.edu.pl
Media społecznościowe
Kontakt
- adakurow@pg.edu.pl
Adiunkt
- Miejsce pracy
- Gmach Elektroniki Telekomunikacji i Informatyki pokój 726
- Telefon
- (58) 347 16 36
Specjalista informatyk
- Miejsce pracy
- Gmach Elektroniki Telekomunikacji i Informatyki pokój 726
- Telefon
- (58) 347 16 36
Wybrane publikacje
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
The approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Analysis of results of large-scale multimodal biometric identity verification experiment
An analysis of a large set of biometric data obtained during the enrolment and the verification phase in an experimental biometric system installed in bank branches is presented. Subjective opinions of bank clients and of bank tellers were also surveyed concerning the studied biometric methods in order to discover and to explore relations emerging from the obtained multimodal dataset. First, data acquisition and identity verification...
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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
The purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
wyświetlono 2342 razy