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This paper presents a speech enhancement technique for signals corrupted by nonstationary acoustic noises. The proposed approach applies the empirical mode decomposition (EMD) to the noisy speech signal and obtains a set of intrinsic mode functions (IMF). The main contribution of the proposed procedure is the adoption of the Hurst exponent in the selection(More)
The " European Transport Solver " (ETS) [1,2] is the new modular simulator developed within the EFDA Integrated Tokamak Modelling (ITM) Task Force*. Ultimately, it will allow for the entire discharge simulation from the start up until the current termination phase, including controllers and subsystems. The paper presents the current status of the project(More)
In this letter, the pH time-frequency vocal source feature is proposed for multistyle emotion identification. A binary acoustic mask is also used to improve the emotion classification accuracy. Emotional and stress conditions from the Berlin Database of Emotional Speech (EMO-DB) and Speech under Simulated and Actual Stress (SUSAS) databases are investigated(More)
This letter proposes a new time domain speech enhancement technique for signals corrupted by nonstationary acoustic noises. In this method, the noise components are detected and attenuated directly from the corrupted speech samples. They are obtained with a robust estimation of the noise standard deviation considering any speech and noise amplitude(More)
This paper investigates the fusion of Mel-frequency cepstral coefficients (MFCC) and statistical pH features to improve the performance of speaker verification (SV) in non-stationary noise conditions. The α-integrated Gaussian Mixture Model (α-GMM) classifier is adopted for speaker modeling. Two different approaches are applied to reduce the(More)
This paper introduces an adaptive noise detection method for non-stationary acoustic noisy signals. The proposed approach is based on the empirical mode decomposition (EMD) and a vector of Hurst exponent coefficients. The scheme is investigated considering real acoustic noisy signals with different non-stationarity degree and signal-to-noise ratio (SNR).(More)
This paper investigates the fusion of Mel-frequency cepstral coefficients (MFCC) and statistical pH features to improve the performance of speaker verification (SV) in non-stationary noise conditions. The α-integrated Gaussian Mixture Model ( α-GMM) classifier is adopted for speaker modeling. Two different approaches are applied to reduce the(More)
  • Fareed Hawwa, B S In, +20 authors Zito
  • 2010
Acknowlegments I would like to thank my dissertation advisor, Professor Jerome W. Hoffman, for all of his guidance and patience. This goal of mine would have never been achieved had it not been for the countless hours he was willing to spend working with me. I am very greatful that he had faith in me from the very beginning. Next, I would like to thank(More)
A robust biometric access system for optical communications based on a speaker identification authentication is proposed in this paper. The solution also enables optical access with remote speaker identification. A set of speech features and classifiers were defined to achieve the best recognition rates. The experiments demonstrated the feasibility and(More)
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