Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Masoud Geravanchizadeh"'
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2021, Iss 1, Pp 1-19 (2021)
Abstract The performance of speech recognition systems trained with neutral utterances degrades significantly when these systems are tested with emotional speech. Since everybody can speak emotionally in the real-world environment, it is necessary to
Externí odkaz:
https://doaj.org/article/fdcd99fd273c4205919c0cdfd12806b3
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Abstract The cocktail party phenomenon describes the ability of the human brain to focus auditory attention on a particular stimulus while ignoring other acoustic events. Selective auditory attention detection (SAAD) is an important issue in the deve
Externí odkaz:
https://doaj.org/article/61a6925d5c0242f5a2e7ad00979805c7
Autor:
Sahar ZAKERI, Masoud GERAVANCHIZADEH
Publikováno v:
Applied Medical Informatics, Vol 43, Iss 1, Pp 24-42 (2021)
Background: In every moment of life, the brain processes a lot of combinations of several sounds. This processing includes stream separation and attended selection, among others. Recent studies show that listener’s attention could be decoded by ana
Externí odkaz:
https://doaj.org/article/2764558fa611438fbdfd2dfe51a73a6a
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2020, Iss 1, Pp 1-15 (2020)
Abstract In real applications, environmental effects such as additive noise and room reverberation lead to a mismatch between training and testing signals that substantially reduces the performance of far-field speaker identification. As a solution t
Externí odkaz:
https://doaj.org/article/ba55e360eb6b4d569872a3aef14f8e08
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2018, Iss 1, Pp 1-13 (2018)
Abstract The performance of automatic speech recognition systems degrades in the presence of emotional states and in adverse environments (e.g., noisy conditions). This greatly limits the deployment of speech recognition application in realistic envi
Externí odkaz:
https://doaj.org/article/203cd72c28264e75b437276c543ac506
Publikováno v:
International Journal of Information and Communication Technology Research, Vol 7, Iss 2, Pp 1-9 (2015)
In this paper, a modified version of an adaptive filtering technique, called fractional affine projection algorithm, is proposed for the dual-channel speech enhancement problem. The new adaptive filtering approach uses the fractional derivative toget
Externí odkaz:
https://doaj.org/article/4ddddc75966a4e96b4828ecbd9f62b63
Publikováno v:
Journal of Advances in Computer Engineering and Technology, Vol 1, Iss 1, Pp 43-50 (2015)
In this paper, we propose a novel algorithm to enhance the noisy speech in the framework of dual-channel speech enhancement. The new method is a hybrid optimization algorithm, which employs the combination of the conventional θ-PSO and the shuffled
Externí odkaz:
https://doaj.org/article/6b84aa4fcdc74d8abeffd49092fb94d3
Publikováno v:
Speech Communication. 132:1-9
The performance of the far-field speaker identification (SI) system is usually reduced by the well-known mismatch problem imposed by environmental conditions. Speech enhancement methods are known as convenient ways of resolving the mismatches created
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2021, Iss 1, Pp 1-19 (2021)
The performance of speech recognition systems trained with neutral utterances degrades significantly when these systems are tested with emotional speech. Since everybody can speak emotionally in the real-world environment, it is necessary to take acc
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2020, Iss 1, Pp 1-15 (2020)
In real applications, environmental effects such as additive noise and room reverberation lead to a mismatch between training and testing signals that substantially reduces the performance of far-field speaker identification. As a solution to this mi