Kontakt:
- email:
- jozkotus@pg.edu.pl
Zajmowane stanowiska:
Profesor uczelni
- miejsce pracy:
- Katedra Systemów Multimedialnych
Gmach Elektroniki Telekomunikacji i Informatyki pokój 729
- telefon:
- (58) 347 29 72

Publikacje:
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This paper presents a method of sound source separation in live audio signals, based on sound intensity analysis. Sound pressure signals recorded with an acoustic vector sensor are analyzed, and the spectral distribution of sound intensity in two dimensions is calculated. Spectral components of the analyzed signal are selected based on the calculated source direction, which leads to a spatial filtration of the sound. The experiments...
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Publikacja
- APPLIED ACOUSTICS - Rok 2025
A method of speech intelligibility improvement in public address (PA) systems installed in reverberant acoustic spaces is proposed. The method is mainly intended for systems operating in high background noise levels. The algorithm is based on the near end listening enhancement approach. Signal-to-noise ratio (SNR) is evaluated in the octave frequency bands. Signal levels in the acoustic space are estimated using the measured impulse...
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Publikacja
This article presents the practical implications of the directional beamforming capability of a higher-order ambisonic microphone compared with popular shotgun microphones. Five different microphones were used in the study: Sennheiser MKH 416, Rode NTG2, Panasonic AG-MC200, Zoom SGH-6, and Zylia ZM-1 (ambisonic microphone). The results highlight the versatility of higher-order ambisonics for non-immersive use, which allows for...
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Publikacja
- Rok 2024
This article presents a case study on the development of a biometric voice verification system for an intercom solution, utilizing the DeepSpeaker neural network architecture. Despite the variety of solutions available in the literature, there is a noted lack of evaluations for "text-independent" systems under real conditions and with varying distances between the speaker and the microphone. This article aims to bridge this gap....
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Publikacja
- Rok 2024
This paper presents a novel approach to enhance the accuracy of deep learning models for acoustic event detection and classification in real-world environments. We introduce a method that leverages activation maps to identify and address model overfitting, combined with an expert-knowledge-based event detection algorithm for data pre-processing. Our approach significantly improved classification performance, increasing the F1 score...
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Projekty:
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Projekty
Kierownik projektu: prof. dr hab. inż. Andrzej Czyżewski Program finansujący: INFOSTRATEG
Projekt realizowany w Katedra Systemów Multimedialnych zgodnie z porozumieniem INFOSTRATEG4/0003/2022 z dnia 2023-05-04
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Projekty
Kierownik projektu: dr hab. inż. Piotr Szczuko Program finansujący: Program Operacyjny Inteligentny Rozwój
Projekt realizowany w Katedra Systemów Multimedialnych zgodnie z porozumieniem POIR.04.01.04-00-0075/19 z dnia 2019-09-24