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Pregled bibliografske jedinice broj: 1143351

Entropy-Based Extraction of Useful Content from Spectrograms of Noisy Speech Signals


Vranković Lacković, Ana; Ipšić, Ivo; Lerga, Jonatan
Entropy-Based Extraction of Useful Content from Spectrograms of Noisy Speech Signals // Proceedings of Elmar-2021 / Muštra, Mario ; Vuković, Josip ; Zovko-Cihlar, Branka (ur.).
Zagreb: Hrvatsko društvo Elektronika u pomorstvu (ELMAR), 2021. str. 83-86 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 1143351 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Entropy-Based Extraction of Useful Content from Spectrograms of Noisy Speech Signals

Autori
Vranković Lacković, Ana ; Ipšić, Ivo ; Lerga, Jonatan

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of Elmar-2021 / Muštra, Mario ; Vuković, Josip ; Zovko-Cihlar, Branka - Zagreb : Hrvatsko društvo Elektronika u pomorstvu (ELMAR), 2021, 83-86

ISBN
978-1-6654-4436-1

Skup
63rd International Symposium ELMAR-2021

Mjesto i datum
Zadar, Hrvatska, 13.09.2021. - 15.09.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Renyi entropy, time-frequency distributions, speech processing

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo



POVEZANOST RADA


Projekti:
IP-2018-01-3739 - Sustav potpore odlučivanju za zeleniju i sigurniju plovidbu brodova (DESSERT) (Prpić-Oršić, Jasna, HRZZ - 2018-01) ( CroRIS)
MINGO-ESIF-KK.01.2.1.02.0179 - ABsistemDCiCloud (ABsistemDCiCloud) (Lerga, Jonatan, MINGO - Fond: Europski fond za regionalni razvoj Program: OP Konkurentnost i kohezija 2014. - 2020. Jačanje gospodarstva primjenom istraživanja i inovacija Područje: IRI - Povećanje razvoja novih proizvoda i usluga koji proizlaze iz aktivnosti istraživanja i raz) ( CroRIS)
VLASTITA-SREDSTVA-uniri-tehnic-17 - Računalom potpomognuta digitalna analiza i klasifikacija signala (UNIRI-TEHNIC-18-17) (Lerga, Jonatan, VLASTITA-SREDSTVA - UNIRI2018) ( CroRIS)
NadSve-Sveučilište u Rijeci-uniri-tehnic-18-15 - Razvoj postupaka temeljenih na strojnom učenju za prepoznavanje bolesti i ozljeda iz medicinskih slika (Štajduhar, Ivan, NadSve ) ( CroRIS)
COST-CA17137 - Mreža za gravitacijske valove, geofiziku i strojno učenje (G2NET) (COST ) ( CroRIS)

Ustanove:
Tehnički fakultet, Rijeka,
Fakultet informatike i digitalnih tehnologija, Rijeka

Profili:

Avatar Url Ana Vranković Lacković (autor)

Avatar Url Jonatan Lerga (autor)

Avatar Url Ivo Ipšić (autor)


Citiraj ovu publikaciju:

Vranković Lacković, Ana; Ipšić, Ivo; Lerga, Jonatan
Entropy-Based Extraction of Useful Content from Spectrograms of Noisy Speech Signals // Proceedings of Elmar-2021 / Muštra, Mario ; Vuković, Josip ; Zovko-Cihlar, Branka (ur.).
Zagreb: Hrvatsko društvo Elektronika u pomorstvu (ELMAR), 2021. str. 83-86 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Vranković Lacković, A., Ipšić, I. & Lerga, J. (2021) Entropy-Based Extraction of Useful Content from Spectrograms of Noisy Speech Signals. U: Muštra, M., Vuković, J. & Zovko-Cihlar, B. (ur.)Proceedings of Elmar-2021.
@article{article, author = {Vrankovi\'{c} Lackovi\'{c}, Ana and Ip\v{s}i\'{c}, Ivo and Lerga, Jonatan}, year = {2021}, pages = {83-86}, keywords = {Renyi entropy, time-frequency distributions, speech processing}, isbn = {978-1-6654-4436-1}, title = {Entropy-Based Extraction of Useful Content from Spectrograms of Noisy Speech Signals}, keyword = {Renyi entropy, time-frequency distributions, speech processing}, publisher = {Hrvatsko dru\v{s}tvo Elektronika u pomorstvu (ELMAR)}, publisherplace = {Zadar, Hrvatska} }
@article{article, author = {Vrankovi\'{c} Lackovi\'{c}, Ana and Ip\v{s}i\'{c}, Ivo and Lerga, Jonatan}, year = {2021}, pages = {83-86}, keywords = {Renyi entropy, time-frequency distributions, speech processing}, isbn = {978-1-6654-4436-1}, title = {Entropy-Based Extraction of Useful Content from Spectrograms of Noisy Speech Signals}, keyword = {Renyi entropy, time-frequency distributions, speech processing}, publisher = {Hrvatsko dru\v{s}tvo Elektronika u pomorstvu (ELMAR)}, publisherplace = {Zadar, Hrvatska} }




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