The Experts below are selected from a list of 9036 Experts worldwide ranked by ideXlab platform
Patrick Kenny - One of the best experts on this subject based on the ideXlab platform.
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EUSIPCO - Spoofing detection employing Infinite Impulse Response — constant Q transform-based feature representations
2017 25th European Signal Processing Conference (EUSIPCO), 2017Co-Authors: Jahangir Alam, Patrick KennyAbstract:Speaker recognition researchers acknowledge that systems which aim to verify speakers automatically based on their pronunciation of an utterance are vulnerable to spoofing attacks using voice conversion and speech synthesis technologies. The first automatic speaker verification spoofing and countermeasures challenge (ASVspoof2015) was designed to stimulate interest in this problem among the speaker recognition communities. In the course of the challenge and subsequently, it became clear that the most effective countermeasures against spoofing attacks are low-level acoustic features (typically extracted at 10 ms intervals) designed to detect artifacts in synthetic or voice converted speech. In this work, we demonstrate the effectiveness of the Infinite Impulse Response — constant Q transform (IIR-CQT) spectrum-based cepstral coefficients (ICQC) as anti-spoofing front-end. The IIR-CQT spectrum is estimated by filtering the multi-resolution fast Fourier transform with an Infinite Impulse Response filter. These features can be used on their own with a standard Gaussian mixture model backend to detect spoofing attacks or they can be used in tandem with bottleneck features which are extracted from a bottleneck layer in a deep neural network designed to discriminate between synthetic and natural speech. We show that the ICQC features are capable of producing very low equal error rates on the individual spoofing attacks in the ASVspoof2015 data set (0.02% on the known attacks, 0.23% on the unknown attacks, and 0.13% on average). Moreover, with a single decision threshold (common to all of the attacks), the ICQC front end yielded an equal error rate of 0.20%.
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spoofing detection employing Infinite Impulse Response constant q transform based feature representations
European Signal Processing Conference, 2017Co-Authors: Jahangir Alam, Patrick KennyAbstract:Speaker recognition researchers acknowledge that systems which aim to verify speakers automatically based on their pronunciation of an utterance are vulnerable to spoofing attacks using voice conversion and speech synthesis technologies. The first automatic speaker verification spoofing and countermeasures challenge (ASVspoof2015) was designed to stimulate interest in this problem among the speaker recognition communities. In the course of the challenge and subsequently, it became clear that the most effective countermeasures against spoofing attacks are low-level acoustic features (typically extracted at 10 ms intervals) designed to detect artifacts in synthetic or voice converted speech. In this work, we demonstrate the effectiveness of the Infinite Impulse Response — constant Q transform (IIR-CQT) spectrum-based cepstral coefficients (ICQC) as anti-spoofing front-end. The IIR-CQT spectrum is estimated by filtering the multi-resolution fast Fourier transform with an Infinite Impulse Response filter. These features can be used on their own with a standard Gaussian mixture model backend to detect spoofing attacks or they can be used in tandem with bottleneck features which are extracted from a bottleneck layer in a deep neural network designed to discriminate between synthetic and natural speech. We show that the ICQC features are capable of producing very low equal error rates on the individual spoofing attacks in the ASVspoof2015 data set (0.02% on the known attacks, 0.23% on the unknown attacks, and 0.13% on average). Moreover, with a single decision threshold (common to all of the attacks), the ICQC front end yielded an equal error rate of 0.20%.
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Spoofing detection employing Infinite Impulse Response — constant Q transform-based feature representations
2017 25th European Signal Processing Conference (EUSIPCO), 2017Co-Authors: Jahangir Alam, Patrick KennyAbstract:Speaker recognition researchers acknowledge that systems which aim to verify speakers automatically based on their pronunciation of an utterance are vulnerable to spoofing attacks using voice conversion and speech synthesis technologies. The first automatic speaker verification spoofing and countermeasures challenge (ASVspoof2015) was designed to stimulate interest in this problem among the speaker recognition communities. In the course of the challenge and subsequently, it became clear that the most effective countermeasures against spoofing attacks are low-level acoustic features (typically extracted at 10 ms intervals) designed to detect artifacts in synthetic or voice converted speech. In this work, we demonstrate the effectiveness of the Infinite Impulse Response - constant Q transform (IIR-CQT) spectrum-based cepstral coefficients (ICQC) as anti-spoofing front-end. The IIR-CQT spectrum is estimated by filtering the multi-resolution fast Fourier transform with an Infinite Impulse Response filter. These features can be used on their own with a standard Gaussian mixture model backend to detect spoofing attacks or they can be used in tandem with bottleneck features which are extracted from a bottleneck layer in a deep neural network designed to discriminate between synthetic and natural speech. We show that the ICQC features are capable of producing very low equal error rates on the individual spoofing attacks in the ASVspoof2015 data set (0.02% on the known attacks, 0.23% on the unknown attacks, and 0.13% on average). Moreover, with a single decision threshold (common to all of the attacks), the ICQC front end yielded an equal error rate of 0.20%.
Shuyuan Yang - One of the best experts on this subject based on the ideXlab platform.
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Robust adaptive Infinite Impulse Response notch filters: a novel state-space approach
2006 IEEE International Symposium on Circuits and Systems, 2006Co-Authors: Junli Liang, Shijun Wang, Shuyuan YangAbstract:In this paper, a robust adaptive Kalman algorithm for a second-order Infinite Impulse Response (IIR) notch filter to detect the frequency of sinusoid signal in the white Gaussian noise is proposed. Firstly, a general expression for the steady-state sinusoid frequency estimation based on minimum mean square error (MMSE) criterion in terms of state-space equations is derived. Secondly, a robust adaptive Kalman algorithm for the state-space equations with unknown noise statistics is given. Finally, computer simulation results are presented to confirm the effectiveness of the proposed algorithm
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ISCAS - Robust adaptive Infinite Impulse Response notch filters: a novel state-space approach
2006 IEEE International Symposium on Circuits and Systems, 2006Co-Authors: Junli Liang, Shijun Wang, Shuyuan YangAbstract:In this paper, a robust adaptive Kalman algorithm for a second-order Infinite Impulse Response (IIR) notch filter to detect the frequency of sinusoid signal in the white Gaussian noise is proposed. Firstly, a general expression for the steady-state sinusoid frequency estimation based on minimum mean square error (MMSE) criterion in terms of state-space equations is derived. Secondly, a robust adaptive Kalman algorithm for the state-space equations with unknown noise statistics is given. Finally, computer simulation results are presented to confirm the effectiveness of the proposed algorithm.
Cheng Yu Chen - One of the best experts on this subject based on the ideXlab platform.
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Frequency stabilization using Infinite Impulse Response filtering for SSFP fMRI at 3T.
Magnetic Resonance in Medicine, 2007Co-Authors: Ming Long Wu, Pei Hsin Wu, Teng-yi Huang, Yi Yu Shih, Ming Chung Chou, Hsiao-wen Chung, Cheng Yu ChenAbstract:The steady-state free precession (SSFP) method has been shown to exhibit strong potential for distortion-free functional magnetic resonance imaging (fMRI). One major challenge of SSFP fMRI is that the frequency band corresponding to the highest functional sensitivity is extremely narrow, leading to substantial loss of functional contrast in the presence of magnetic field drifts. In this study we propose a frequency stabilization scheme whereby an RF pulse with small flip angle is applied before each image scan, and the initial phase of the free induction decay (FID) signals is extracted to reflect temporal field drifts. A simple Infinite Impulse Response (IIR) filter is further employed to obtain a low-pass-filtered estimate of the central reference frequency for the upcoming scan. Experimental results suggest that the proposed scheme can stabilize the frequency settings in accordance with field drifts, with oscillation amplitudes of
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frequency stabilization using Infinite Impulse Response filtering for ssfp fmri at 3t
Magnetic Resonance in Medicine, 2007Co-Authors: Ming Long Wu, Pei Hsin Wu, Teng-yi Huang, Yi Yu Shih, Ming Chung Chou, Hsiao-wen Chung, Cheng Yu ChenAbstract:The steady-state free precession (SSFP) method has been shown to exhibit strong potential for distortion-free functional magnetic resonance imaging (fMRI). One major challenge of SSFP fMRI is that the frequency band corresponding to the highest functional sensitivity is extremely narrow, leading to substantial loss of functional contrast in the presence of magnetic field drifts. In this study we propose a frequency stabilization scheme whereby an RF pulse with small flip angle is applied before each image scan, and the initial phase of the free induction decay (FID) signals is extracted to reflect temporal field drifts. A simple Infinite Impulse Response (IIR) filter is further employed to obtain a low-pass-filtered estimate of the central reference frequency for the upcoming scan. Experimental results suggest that the proposed scheme can stabilize the frequency settings in accordance with field drifts, with oscillation amplitudes of <0.5 Hz. Phantom studies showed that both slow drifts and fast fluctuations were prominently reduced, resulting in less than 5% signal variations. Visual fMRI at submillimeter in-plane resolution further demonstrated 15% activation signals that were nicely registered in the microvessels within the sulci. It is concluded that the IIR-filtered frequency stabilization is an effective technique for achieving reliable SSFP fMR images at high field strengths. Magn Reson Med 57:369–379, 2007. © 2007 Wiley-Liss, Inc.
Balazs Bank - One of the best experts on this subject based on the ideXlab platform.
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converting Infinite Impulse Response filters to parallel form tips tricks
IEEE Signal Processing Magazine, 2018Co-Authors: Balazs BankAbstract:Discrete-time rational transfer functions are often converted to parallel second-order sections due to better numerical performance compared to direct form Infinite Impulse Response (IIR) implementations. This is usually done by performing partial fraction expansion over the original transfer function. When the order of the numerator polynomial is greater or equal to that of the denominator, polynomial long division is applied before partial fraction expansion resulting in a parallel finite Impulse Response (FIR) path.
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Converting Infinite Impulse Response Filters to Parallel Form [Tips & Tricks]
IEEE Signal Processing Magazine, 2018Co-Authors: Balazs BankAbstract:Discrete-time rational transfer functions are often converted to parallel second-order sections due to better numerical performance compared to direct form Infinite Impulse Response (IIR) implementations. This is usually done by performing partial fraction expansion over the original transfer function. When the order of the numerator polynomial is greater or equal to that of the denominator, polynomial long division is applied before partial fraction expansion resulting in a parallel finite Impulse Response (FIR) path.
Ming Chung Chou - One of the best experts on this subject based on the ideXlab platform.
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Frequency stabilization using Infinite Impulse Response filtering for SSFP fMRI at 3T.
Magnetic Resonance in Medicine, 2007Co-Authors: Ming Long Wu, Pei Hsin Wu, Teng-yi Huang, Yi Yu Shih, Ming Chung Chou, Hsiao-wen Chung, Cheng Yu ChenAbstract:The steady-state free precession (SSFP) method has been shown to exhibit strong potential for distortion-free functional magnetic resonance imaging (fMRI). One major challenge of SSFP fMRI is that the frequency band corresponding to the highest functional sensitivity is extremely narrow, leading to substantial loss of functional contrast in the presence of magnetic field drifts. In this study we propose a frequency stabilization scheme whereby an RF pulse with small flip angle is applied before each image scan, and the initial phase of the free induction decay (FID) signals is extracted to reflect temporal field drifts. A simple Infinite Impulse Response (IIR) filter is further employed to obtain a low-pass-filtered estimate of the central reference frequency for the upcoming scan. Experimental results suggest that the proposed scheme can stabilize the frequency settings in accordance with field drifts, with oscillation amplitudes of
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frequency stabilization using Infinite Impulse Response filtering for ssfp fmri at 3t
Magnetic Resonance in Medicine, 2007Co-Authors: Ming Long Wu, Pei Hsin Wu, Teng-yi Huang, Yi Yu Shih, Ming Chung Chou, Hsiao-wen Chung, Cheng Yu ChenAbstract:The steady-state free precession (SSFP) method has been shown to exhibit strong potential for distortion-free functional magnetic resonance imaging (fMRI). One major challenge of SSFP fMRI is that the frequency band corresponding to the highest functional sensitivity is extremely narrow, leading to substantial loss of functional contrast in the presence of magnetic field drifts. In this study we propose a frequency stabilization scheme whereby an RF pulse with small flip angle is applied before each image scan, and the initial phase of the free induction decay (FID) signals is extracted to reflect temporal field drifts. A simple Infinite Impulse Response (IIR) filter is further employed to obtain a low-pass-filtered estimate of the central reference frequency for the upcoming scan. Experimental results suggest that the proposed scheme can stabilize the frequency settings in accordance with field drifts, with oscillation amplitudes of <0.5 Hz. Phantom studies showed that both slow drifts and fast fluctuations were prominently reduced, resulting in less than 5% signal variations. Visual fMRI at submillimeter in-plane resolution further demonstrated 15% activation signals that were nicely registered in the microvessels within the sulci. It is concluded that the IIR-filtered frequency stabilization is an effective technique for achieving reliable SSFP fMR images at high field strengths. Magn Reson Med 57:369–379, 2007. © 2007 Wiley-Liss, Inc.
