Pregled bibliografske jedinice broj: 528318
Emotional Speech Corpus of Croatian Language
Emotional Speech Corpus of Croatian Language // 7th International Symposium on Image and Signal Processing and Analysis / Sven Lončarić, Gianni Ramponi, Damir Seršić (ur.).
Zagreb: Fakultet elektrotehnike i računarstva Sveučilišta u Zagrebu, 2011. str. 95-100 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 528318 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Emotional Speech Corpus of Croatian Language
Autori
Dropuljić, Branimir ; Thomasz Chmura, Miłosz ; Kolak, Antonio ; Petrinović, Davor
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
7th International Symposium on Image and Signal Processing and Analysis
/ Sven Lončarić, Gianni Ramponi, Damir Seršić - Zagreb : Fakultet elektrotehnike i računarstva Sveučilišta u Zagrebu, 2011, 95-100
ISBN
978-953-184-159-7
Skup
7th International Symposium on Image and Signal Processing and Analysis (ISPA 2011)
Mjesto i datum
Dubrovnik, Hrvatska, 04.09.2011. - 06.09.2011
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
emotional speech corpus; Croatian language; affective speech; acoustic features; linguistic features; automatic emotion recognition; automatic speech recognition
Sažetak
As a first step in developing an emotion recognition system from human voice, it is necessary to collect relevant set of emotionally rich utterances that will be used for system training. Thus, a first emotional speech corpus of Croatian language (KEG) was built and annotated. The collection and annotation process together with some interesting statistical properties of the designed corpus are described in this paper. Utterances were collected from both male and female speakers, from child age to adults, verbally expressing their emotions. Materials were taken from Internet and other public media sources, with the total duration of approximately 40 minutes. Emotion classification used for annotation has been based on 5 discrete emotional states: happiness, sadness, fear, anger and neutral state. For each of the non-neutral emotional states, the perceived intensity was also annotated in 10 steps. Preliminary KEG evaluation was performed by building and testing an emotion recognition system based on this specific corpus. Initial results are presented in this paper.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
POVEZANOST RADA
Projekti:
0036054
036-0000000-2029 - Adaptivno upravljanje scenarijima u VR terapiji PTSP-a (Ćosić, Krešimir, MZO ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
