Multi-Stage Recognition of Speech Emotion Using Sequential Forward Feature Selection

Autor: Liogienė Tatjana, Tamulevičius Gintautas

Publikováno v: Electrical, Control and Communication Engineering, Vol 10, Iss 1, Pp 35-41 (2016)

The intensive research of speech emotion recognition introduced a huge collection of speech emotion features. Large feature sets complicate the speech emotion recognition task. Among various feature selection and transformation techniques for one-sta

Externí odkaz: https://doaj.org/article/00e21e8e8d8c4ff28dc562d89c2b0ff8

Improving Speech Recognition Rate through Analysis Parameters

Autor: Eringis Deividas, Tamulevičius Gintautas

Publikováno v: Electrical, Control and Communication Engineering, Vol 5, Iss 1, Pp 61-66 (2014)

Speech signal is redundant and non-stationary by nature. Because of vocal tract inertness these variations are not very rapid and the signal can be considered as stationary in short segments. It is presumed that in short-time magnitude spectrum the m

Externí odkaz: https://doaj.org/article/dda5cb399cb942ad8d681b4fe96457d9

Are We Able to Model the Human Auditory System in Speech Signal Enhancement?

Autor: Zakševski, Daniel, Tamulevičius, Gintautas

Publikováno v: Vilnius University Proceedings; 2024, Vol. 52, p132-132, 1p

Acoustic analysis for vocal fold assessment - challenges, trends, and opportunities

Autor: Danilovaitė, Monika, Tamulevičius, Gintautas

Publikováno v: DAMSS: 12th conference on data analysis methods for software systems, Druskininkai, Lithuania, December 2–4, 2021, Vilnius : Vilnius University Press, 2021, p. 12

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______4036::a9a55fc12ba5b218a693fa1af35ab920
https://repository.vu.lt/VU:ELABAPDB113435516&prefLang=en_US

The impact of data augmentation based on white noise for noise-robust CNN-based speech recognition

Autor: Tamulevičius, Gintautas, Korvel, Gražina, Bernatavičienė, Jolita, Treigys, Povilas

Publikováno v: 11th international workshop on data analysis methods for software systems (DAMSS 2019), Druskininkai, Lithuania, November 28-30, 2019 / Lithuanian Computer Society, Vilnius University Institute of Data Science and Digital Technologies, Lithuanian Academy of Sciences, Vilnius : Vilnius University Press, 2019, p. 83-84

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::9b8eeae545011343ca51a43f16a01b3c
https://repository.vu.lt/VU:ELABAPDB54763435&prefLang=en_US