Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Cenk SEZGIN"'
Publikováno v:
Speech Communication. 67:26-41
We propose a method based on perceptual prosodic features for medium term speaker state classification, particularly sleepiness detection. Unlike existing methods, our features represent spectral characteristics of speech in perceptual bands and also
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d530bdbc6d6e712c177bd64b44d0edb9
https://doi.org/10.1016/j.specom.2014.09.002
https://doi.org/10.1016/j.specom.2014.09.002
Publikováno v:
ICASSP
We propose a two-class classification scheme with a small number of features for sleepiness detection. Unlike the conventional methods that rely on the linguistics content of speech, we work with prosodic features extracted by psychoacoustic masking
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::785a51e8c4dc98d5e0b070fe561d9960
https://doi.org/10.1109/icassp.2013.6637756
https://doi.org/10.1109/icassp.2013.6637756
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing. 2012
In this article, we propose a new set of acoustic features for automatic emotion recognition from audio. The features are based on the perceptual quality metrics that are given in perceptual evaluation of audio quality known as ITU BS.1387 recommenda
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::305e89dfe177891b0ad56515cd5d6591
https://doi.org/10.1186/1687-4722-2012-16
https://doi.org/10.1186/1687-4722-2012-16
Publikováno v:
2012 20th Signal Processing and Communications Applications Conference (SIU).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7bc660d88f30e57fbfe85199878d651
https://doi.org/10.1109/siu.2012.6204832
https://doi.org/10.1109/siu.2012.6204832
Publikováno v:
SIU
A 9-D perceptual feature set has been used for audio emotion recognition. Performance tests have been performed on well known EMO-DB and VAM databases and the results are reported for different classifiers. Support Vector Machines, Gaussian Mixture M
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7694daae385dc41f0936d47a469be8c4
https://doi.org/10.1109/siu.2012.6204799
https://doi.org/10.1109/siu.2012.6204799
Publikováno v:
2011 IEEE 19th Signal Processing and Communications Applications Conference (SIU).
Our aim in this paper is to illustrate the effectiveness of the Dirichlet Process Mixture (DPM) model for emotional speech class density estimation when the number of Gauss mixture components are unknown. The problem is modeled as a two-class classif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e1555a38c141c73a0d4027b928aad13
https://doi.org/10.1109/siu.2011.5929820
https://doi.org/10.1109/siu.2011.5929820
Publikováno v:
FG
We present a novel system for audio emotion recognition based on the Perceptual Evaluation of Audio Quality (PEAQ) model as described by the standard, ITU-R BS.1387–1 which provides a mathematical model resembling the human auditory system. The int
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::882ea516fd4586bb67202f9980ef39dc
https://doi.org/10.1109/fg.2011.5771348
https://doi.org/10.1109/fg.2011.5771348
Publikováno v:
Viral Hepatitis Journal, Vol 8, Iss 1 (2003)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doajarticles::353041bce62b8eb68840809baed65a01
https://doaj.org/article/362a1add1ad349f99ef5e165608cc50f
https://doaj.org/article/362a1add1ad349f99ef5e165608cc50f