Browsing by Subject "Gaussian processes"
Now showing items 1-8 of 8
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Gauss karışım modeli tabanlı konuşmacı belirleme sistemlerinde klasik MAP uyarlanması yönteminin performans analizi
(IEEE, 2010)Gaussian mixture models (GMM) is one of the most commonly used methods in text-independent speaker identification systems. In this paper, performance of the GMM approach has been measured with different parameters and ... -
Gauss karışım modeli tabanlı konuşmacı doğrulama sistemlerinde kişiye ve kanala uyarlanmada klasik MAP tabanlı yöntemlerin performans analizi
(IEEE, 2011)In this paper, performance of Gaussian mixture models (GMM) based algorithms implemented in Speech Processing Laboratory at Ozyegin University, within NIST SRE2004 and 2006 database was reported. Gaussian mixture models ... -
INTERSPEECH 2009 duygu tanıma yarışması değerlendirmesi
(IEEE, 2010)Bu makalede INTERSPEECH 2009 Duygu Tanıma Yarışması sonuçlarını değerlendiriyoruz. Yarışmanın sunduğu problem doğal ve duygu bakımından zengin FAU Aibo konuşma kayıtlarının beş ve iki duygu sınıfına en doğru şekilde ... -
Sparse channel estimation for OFDM-based underwater cooperative systems with amplify-and-forward relaying
(IEEE, 2014)This paper is concerned with a challenging problem of channel estimation for amplify-and-forward cooperative relay based orthogonal frequency division multiplexing (OFDM) systems in the presence of sparse underwater acoustic ... -
Spectrum sensing of correlated subbands with colored noise in cognitive radios
(IEEE, 2012)In this paper, we consider the problem of wideband spectrum sensing by using the correlation among the observation samples in different subbands. The Primary User (PU) signal samples in occupied subbands are assumed to be ... -
Supervising topic models with Gaussian processes
(Elsevier, 2018-05)Topic modeling is a powerful approach for modeling data represented as high-dimensional histograms. While the high dimensionality of such input data is extremely beneficial in unsupervised applications including language ... -
Use of line spectral frequencies for emotion recognition from speech
(IEEE, 2010)We propose the use of the line spectral frequency (LSF) features for emotion recognition from speech, which have not been been previously employed for emotion recognition to the best of our knowledge. Spectral features ... -
Variational bayesian multiple instance learning with gaussian processes
(IEEE, 2017)Gaussian Processes (GPs) are effective Bayesian predictors. We here show for the first time that instance labels of a GP classifier can be inferred in the multiple instance learning (MIL) setting using variational Bayes. ...
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