prof. dr hab. inż. Bożena Kostek
Zatrudnienie
- Kierownik Laboratorium w Laboratorium Akustyki Fonicznej
- Profesor w Laboratorium Akustyki Fonicznej
Kontakt dla biznesu
- Lokalizacja
- Al. Zwycięstwa 27, 80-219 Gdańsk
- Telefon
- +48 58 348 62 62
- biznes@pg.edu.pl
Media społecznościowe
Kontakt
- bozena.kostek@pg.edu.pl
Profesor
- Miejsce pracy
-
Budynek A Elektroniki
pokój EA 731 otwiera się w nowej karcie - Telefon
- (58) 347 27 17
- bokostek@audioakustyka.org
Wybrane publikacje
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An audio-visual corpus for multimodal automatic speech recognition
review of available audio-visual speech corpora and a description of a new multimodal corpus of English speech recordings is provided. The new corpus containing 31 hours of recordings was created specifically to assist audio-visual speech recognition systems (AVSR) development. The database related to the corpus includes high-resolution, high-framerate stereoscopic video streams from RGB cameras, depth imaging stream utilizing Time-of-Flight...
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Automatic music genre classification based on musical instrument track separation / Automatyczna klasyfikacja gatunku muzycznego wykorzystująca algorytm separacji dźwięku instrumentó muzycznych
The aim of this article is to investigate whether separating music tracks at the pre-processing phase and extending feature vector by parameters related to the specific musical instruments that are characteristic for the given musical genre allow for efficient automatic musical genre classification in case of database containing thousands of music excerpts and a dozen of genres. Results of extensive experiments show that the approach...
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Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
convolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...
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