Entropy-Based Extraction of Useful Content from Spectrograms of Noisy Speech Signals (CROSBI ID 706690)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Vranković Lacković, Ana ; Ipšić, Ivo ; Lerga, Jonatan
engleski
Entropy-Based Extraction of Useful Content from Spectrograms of Noisy Speech Signals
In the paper, we extend and apply the 2D local entropy method (2DLEM) used for signal time- frequency representation to useful content extraction from noisy speech signals. In our previous work, we presented the 2D local entropy method (2DLEM) and tested it on synthetic signals and a small number of real-world signals. We now extend the application of our method by applying it to recorded speech signals combined with noise from different sources. The database we used is commonly used in speech recognition, where tested methods usually have the best result achieved on clean signals without added noise or on denoised signals. The 2DLEM method is used for the extraction of useful content, and in this paper, we test it in realworld scenarios. Our results show promising results for all tested signals regardless of the noise source or signal- to-noise ratios (SNRs). Combining the 2DLEM method with speech recognition methods could improve the performance of speech recognition and understanding systems.
Renyi entropy, time-frequency distributions, speech processing
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Podaci o prilogu
83-86.
2021.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of Elmar-2021
Muštra, Mario ; Vuković, Josip ; Zovko-Cihlar, Branka
Zagreb: Hrvatsko društvo Elektronika u pomorstvu (ELMAR)
978-1-6654-4436-1
Podaci o skupu
63rd International Symposium ELMAR 2021
predavanje
12.09.2021-15.09.2021
Zadar, Hrvatska