The Experts below are selected from a list of 288 Experts worldwide ranked by ideXlab platform
Israel Cohen - One of the best experts on this subject based on the ideXlab platform.
-
Relative Transfer Function Identification Using Convolutive Transfer Function Approximation
IEEE Transactions on Audio Speech and Language Processing, 2009Co-Authors: Ronen Talmon, Israel Cohen, Sharon GannotAbstract:In this paper, we present a relative Transfer Function (RTF) identification method for speech sources in reverberant environments. The proposed method is based on the convolutive Transfer Function (CTF) approximation, which enables to represent a linear convolution in the time domain as a linear convolution in the short-time Fourier transform (STFT) domain. Unlike the restrictive and commonly used multiplicative Transfer Function (MTF) approximation, which becomes more accurate when the length of a time frame increases relative to the length of the impulse response, the CTF approximation enables representation of long impulse responses using short time frames. We develop an unbiased RTF estimator that exploits the nonstationarity and presence probability of the speech signal and derive an analytic expression for the estimator variance. Experimental results show that the proposed method is advantageous compared to common RTF identification methods in various acoustic environments, especially when identifying long RTFs typical to real rooms.
-
Multichannel speech enhancement using convolutive Transfer Function approximation in reverberant environments
2009 IEEE International Conference on Acoustics Speech and Signal Processing, 2009Co-Authors: Ronen Talmon, Israel Cohen, Sharon GannotAbstract:Recently, we have presented a Transfer-Function generalized sidelobe canceler (TF-GSC) beamformer in the short time Fourier transform domain, which relies on a convolutive Transfer Function approximation of relative Transfer Functions between distinct sensors. In this paper, we combine a delay-and-sum beamformer with the TF-GSC structure in order to suppress the speech signal reflections captured at the sensors in reverberant environments. We demonstrate the performance of the proposed beamformer and compare it with the TF-GSC. We show that the proposed algorithm enables suppression of reverberations and further noise reduction compared with the TF-GSC beamformer.
-
relative Transfer Function identification using speech signals
IEEE Transactions on Speech and Audio Processing, 2004Co-Authors: Israel CohenAbstract:An important component of a multichannel hands-free communication system is the identification of the relative Transfer Function between sensors in response to a desired source signal. In this paper, a robust system identification approach adapted to speech signals is proposed. A weighted least-squares optimization criterion is introduced, which considers the uncertainty of the desired signal presence in the observed signals. An asymptotically unbiased estimate for the system's Transfer Function is derived, and a corresponding recursive online implementation is presented. We show that compared to a competing nonstationarity-based method, a smaller error variance is achieved and generally shorter observation intervals are required. Furthermore, in the case of a time-varying system, faster convergence and higher reliability of the system identification are obtained by using the proposed method than by using the nonstationarity-based method. Evaluation of the proposed system identification approach is performed under various noise conditions, including simulated stationary and nonstationary white Gaussian noise, and car interior noise in real pseudo-stationary and nonstationary environments. The experimental results confirm the advantages of proposed approach.
Sharon Gannot - One of the best experts on this subject based on the ideXlab platform.
-
Relative Transfer Function Identification Using Convolutive Transfer Function Approximation
IEEE Transactions on Audio Speech and Language Processing, 2009Co-Authors: Ronen Talmon, Israel Cohen, Sharon GannotAbstract:In this paper, we present a relative Transfer Function (RTF) identification method for speech sources in reverberant environments. The proposed method is based on the convolutive Transfer Function (CTF) approximation, which enables to represent a linear convolution in the time domain as a linear convolution in the short-time Fourier transform (STFT) domain. Unlike the restrictive and commonly used multiplicative Transfer Function (MTF) approximation, which becomes more accurate when the length of a time frame increases relative to the length of the impulse response, the CTF approximation enables representation of long impulse responses using short time frames. We develop an unbiased RTF estimator that exploits the nonstationarity and presence probability of the speech signal and derive an analytic expression for the estimator variance. Experimental results show that the proposed method is advantageous compared to common RTF identification methods in various acoustic environments, especially when identifying long RTFs typical to real rooms.
-
Multichannel speech enhancement using convolutive Transfer Function approximation in reverberant environments
2009 IEEE International Conference on Acoustics Speech and Signal Processing, 2009Co-Authors: Ronen Talmon, Israel Cohen, Sharon GannotAbstract:Recently, we have presented a Transfer-Function generalized sidelobe canceler (TF-GSC) beamformer in the short time Fourier transform domain, which relies on a convolutive Transfer Function approximation of relative Transfer Functions between distinct sensors. In this paper, we combine a delay-and-sum beamformer with the TF-GSC structure in order to suppress the speech signal reflections captured at the sensors in reverberant environments. We demonstrate the performance of the proposed beamformer and compare it with the TF-GSC. We show that the proposed algorithm enables suppression of reverberations and further noise reduction compared with the TF-GSC beamformer.
Bob Gravelle - One of the best experts on this subject based on the ideXlab platform.
-
off axis sensor modulation Transfer Function measurement using band limited laser speckle
Frontiers in Optics 2009 Laser Science XXV Fall 2009 OSA Optics & Photonics Technical Digest (2009) paper CThB6, 2009Co-Authors: Xi Chen, Doug Fettig, Bob Gravelle, Gennadiy AgranovAbstract:We present a new methodology for measurement of off-axis sensor modulation Transfer Function using band-limited laser speckle and two-dimensional generalized sampling theorem. The effect of chief ray angle on sensor modulation Transfer Function is studied.
-
sensor modulation Transfer Function measurement using band limited laser speckle
Optics Express, 2008Co-Authors: Xi Chen, Gennadiy Agranov, Nicholas George, Bob GravelleAbstract:A new methodology for image sensor modulation Transfer Function measurement using band-limited laser speckle is presented. We use a circular opal milk glass diffuser illuminated by a 5mW He-Ne laser and a linear polarizer to generate band-limited speckle on the sensor. The power spectral density cut-off frequency of the speckle is chosen to be twice that of the sensor Nyquist frequency by placing the sensor at the specific Z location along the optical axis. For the speckle input, we calculate the power spectral density at the sensor using the Rayleigh-Sommerfeld integral and then measure the output power spectral density for the speckle pattern captured by the sensor. With these data, the two-dimensional image sensor modulation Transfer Function (MTF) is calculated.
Ronen Talmon - One of the best experts on this subject based on the ideXlab platform.
-
Relative Transfer Function Identification Using Convolutive Transfer Function Approximation
IEEE Transactions on Audio Speech and Language Processing, 2009Co-Authors: Ronen Talmon, Israel Cohen, Sharon GannotAbstract:In this paper, we present a relative Transfer Function (RTF) identification method for speech sources in reverberant environments. The proposed method is based on the convolutive Transfer Function (CTF) approximation, which enables to represent a linear convolution in the time domain as a linear convolution in the short-time Fourier transform (STFT) domain. Unlike the restrictive and commonly used multiplicative Transfer Function (MTF) approximation, which becomes more accurate when the length of a time frame increases relative to the length of the impulse response, the CTF approximation enables representation of long impulse responses using short time frames. We develop an unbiased RTF estimator that exploits the nonstationarity and presence probability of the speech signal and derive an analytic expression for the estimator variance. Experimental results show that the proposed method is advantageous compared to common RTF identification methods in various acoustic environments, especially when identifying long RTFs typical to real rooms.
-
Multichannel speech enhancement using convolutive Transfer Function approximation in reverberant environments
2009 IEEE International Conference on Acoustics Speech and Signal Processing, 2009Co-Authors: Ronen Talmon, Israel Cohen, Sharon GannotAbstract:Recently, we have presented a Transfer-Function generalized sidelobe canceler (TF-GSC) beamformer in the short time Fourier transform domain, which relies on a convolutive Transfer Function approximation of relative Transfer Functions between distinct sensors. In this paper, we combine a delay-and-sum beamformer with the TF-GSC structure in order to suppress the speech signal reflections captured at the sensors in reverberant environments. We demonstrate the performance of the proposed beamformer and compare it with the TF-GSC. We show that the proposed algorithm enables suppression of reverberations and further noise reduction compared with the TF-GSC beamformer.
Xi Chen - One of the best experts on this subject based on the ideXlab platform.
-
off axis sensor modulation Transfer Function measurement using band limited laser speckle
Frontiers in Optics 2009 Laser Science XXV Fall 2009 OSA Optics & Photonics Technical Digest (2009) paper CThB6, 2009Co-Authors: Xi Chen, Doug Fettig, Bob Gravelle, Gennadiy AgranovAbstract:We present a new methodology for measurement of off-axis sensor modulation Transfer Function using band-limited laser speckle and two-dimensional generalized sampling theorem. The effect of chief ray angle on sensor modulation Transfer Function is studied.
-
sensor modulation Transfer Function measurement using band limited laser speckle
Optics Express, 2008Co-Authors: Xi Chen, Gennadiy Agranov, Nicholas George, Bob GravelleAbstract:A new methodology for image sensor modulation Transfer Function measurement using band-limited laser speckle is presented. We use a circular opal milk glass diffuser illuminated by a 5mW He-Ne laser and a linear polarizer to generate band-limited speckle on the sensor. The power spectral density cut-off frequency of the speckle is chosen to be twice that of the sensor Nyquist frequency by placing the sensor at the specific Z location along the optical axis. For the speckle input, we calculate the power spectral density at the sensor using the Rayleigh-Sommerfeld integral and then measure the output power spectral density for the speckle pattern captured by the sensor. With these data, the two-dimensional image sensor modulation Transfer Function (MTF) is calculated.
