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19th Annual Conference of the International-Speech-Communication-Association (INTERSPEECH 2018)

作者： Kamble, Madhu R. Patil, Hemant A. DA IICT Speech Res Lab Gandhinagar Gujarat India

ISBN: (纸本)9781510872219

Voice-based speaker authentication or Automatic Speaker Verification (ASV) system is now becoming practical reality after several decades of research. However, still this technology is very much susceptible to various spoofing attacks. Among various spoofing attacks, replay is the most challenging attack. In this paper, we propose a novel feature set based on our recently introduced Variable length energy separation algorithm (VESA) during INTERSPEECH 2017. The key idea of this paper is to capture the Instantaneous Amplitude (IA) obtained from the instantaneous energy fluctuations. The replay speech is affected by acoustic environment and distortions of intermediate device. Thus, the noise added in replayed speech is important to detect. The Amplitude Modulations (AM) are more susceptible to noise and multipath interferences that may result due to replay mechanism. The experiments are performed on various dependency index (DI) and lower EER of 6.12 % and 11.94 % is found on dev and eval set, respectively, of ASV Spoof 2017 Challenge database. Furthermore, we compare our results with CQCC, LFCC, MFCC, and VESA-IFCC feature sets. The score-level fusion VESA-IFCC and proposed feature set further reduced the EER to 0.19 % and 7.11 % on dev and eval set, respectively.

关键词： Automatic Speaker Verification Spoofing energy separation algorithm Instantaneous Amplitude

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Modal parameter identification of tall buildings based on variational mode decomposition and energy separation

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WIND AND STRUCTURES 2023年第6期37卷 445-460页

作者： Cai, Kang Huang, Mingfeng Li, Xiao Xu, Haiwei Li, Binbin Yang, Chen Zhejiang Univ Coll Civil Engn & Architecture Inst Struct Engn Hangzhou 310058 Peoples R China Zhejiang Univ Ctr Balance Architecture Hangzhou 310058 Peoples R China Univ Genoa Polytech Sch Dept Civil Chem & Environm Engn Via Montallegro 1 I-16145 Genoa Italy Zhejiang Univ Coll Civil Engn & Architecture Hangzhou 310058 Zhejiang Peoples R China Zhejiang Univ ZJU UIUC Inst Haining 314400 Peoples R China

Accurate estimation of modal parameters (i.e., natural frequency, damping ratio) of tall buildings is of great importance to their structural design, structural health monitoring, vibration control, and state assessment. Based on the combination of variational mode decomposition, smoothed discrete energy separation algorithm -1, and Half -cycle energy operator (VMD-SH), this paper presents a method for structural modal parameter estimation. The variational mode decomposition is proved to be effective and reliable for decomposing the mixed -signal with low frequencies and damping ratios, and the validity of both smoothed discrete energy separation algorithm -1 and Half -cycle energy operator in the modal identification of a single modal system is verified. By incorporating these techniques, the VMD-SH method is able to accurately identify and extract the various modes present in a signal, providing improved insights into its underlying structure and behavior. Subsequently, a numerical study of a four-story frame structure is conducted using the Newmark-beta method, and it is found that the relative errors of natural frequency and damping ratio estimated by the presented method are much smaller than those by traditional methods, validating the effectiveness and accuracy of the combined method for the modal identification of the multimodal system. Furthermore, the presented method is employed to estimate modal parameters of a full-scale tall building utilizing acceleration responses. The identified results verify the applicability and accuracy of the presented VMD-SH method in field measurements. The study demonstrates the effectiveness and robustness of the proposed VMD-SH method in accurately estimating modal parameters of tall buildings from acceleration response data.

关键词： damping ratio energy separation algorithm modal parameter identification natural frequency variational mode decomposition

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energy separation Based Instantaneous Frequency Estimation from Quadrature and In-Phase Components for Replay Spoof Detection 30

Energy Separation Based Instantaneous Frequency Estimation f...

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30th European Signal Processing Conference (EUSIPCO)

作者： Gupta, Priyanka Chodingala, Piyushkumar K. Patil, Hemant A. DA IICT Gandhinagar Speech Res Lab Gandhinagar Gujarat India

ISBN: (纸本)9789082797091

For replay Spoof Speech Detection (SSD), features that incorporate auditory transform-based information as well as Instantaneous Frequency (IF) information have been proposed in the past. IF is estimated either by derivative of analytic phase via Hilbert transform, or by using high temporal resolution Teager energy Operator (TEO)-based energy separation algorithm (ESA). However, the excellent temporal resolution of ESA comes with lacking in using relative phase information, and vice-versa. Hence, we propose novel CFCCIF-QESA features, with excellent temporal resolution as well as relative phase information. CFCCIF-QESA is designed by exploiting relative phase shift, without estimating phase explicitly. Effectiveness of proposed approach is validated by mutual information and Kullback-Leibler (KL) divergence-based analysis. Furthermore, TEO is used for complex signals for SSD. Consequently, the novel ideas of quadrature relative phase and TEO for complex signals are exploited for improving the performance of CFCCIF-ESA on ASVspoof 2017 version2.0 and ASVspoof 2019 databases. On ASVspoof 2017 evaluation set, when compared with CQCC features, CFCCIF-QESA features yield percentage improvement of 35.51% and 30.19%, with GMM and CNN classifiers, respectively. As compared to CFCCIF-ESA, a percentage improvement of 30.40% is achieved on ASVspoof 2019 evaluation dataset with GMM. Finally, the analysis of latency period indicates relatively better performance of CFCCIF-QESA and thus, its potential for practical SSD system deployment.

关键词： Quadrature phase Mutual Information KL divergence energy separation algorithm Instantaneous Frequency

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Relevance of Quadrature Phase For Replay Detection in Voice Assistants (VAs)

Relevance of Quadrature Phase For Replay Detection in Voice ...

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Asia-Pacific-Signal-and-Information-Processing-Association Annual Summit and Conference (APSIPA ASC)

作者： Gupta, Priyanka Chodingala, Piyushkumar K. Patil, Hemant A. DA IICT Gandhinagar India

ISBN: (纸本)9798350300673

There have been various studies involving Instantaneous Frequency (IF) estimation for Spoofed Speech Detection (SSD) task, such as the derivative of the phase obtained by Hilbert Transform (HT) approach and energy separation-based method. However, IF estimation by HT leads to lack of good temporal resolution. On the other hand, ESA-based method leads to excellent time resolution, however, lacks the relative phase information. Therefore, in this paper, we have proposed Cochlear Filter Cepstral Coefficients-based Instantaneous Frequency using Quadrature energy separation algorithm (CFCCIF-QESA) feature set, which merits of having an excellent time resolution as well as inclusion of the relative phase information. Hence, we illustrate the significance of incorporating the quadrature-phase component along with the in-phase component for SSD of replay detection in VAs. To that effect, we perform experiments on the Realistic Replay AttackF Microphone-Array Speech Corpus (ReMASC) dataset. Furthermore, the proposed CFCCIF-QESA feature set gives 28.71 and 29.89 %EER using GMM and CNN respectively, on Eval set. The proposed feature set is evaluated using various performance metrics, including EER and other confusion matrix-based metrics. Finally, the latency for CFCCIF-QESA and CFCCIF-ESA is presented, showing the better suitability of the proposed CFCCIF-QESA feature set w.r.t. practical deployment.

关键词： Spoofed Speech Detection Mutual Information Quadrature Phase energy separation algorithm

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Significance of Quadrature and In-Phase Components for Synthetic Spoofed Speech Detection

Significance of Quadrature and In-Phase Components for Synth...

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14th Annual Summit and Conference of the Asia-Pacific-Signal-and-Information-Processing-Association (APSIPA ASC)

作者： Gupta, Priyanka Chodingala, Piyushkumar K. Patil, Hemant A. Dhirubhai Ambani Inst Informat & Commun Technol I Gandhinagar India

ISBN: (数字)9786165904773

ISBN: (纸本)9786165904773

For synthetic and voice converted Spoofed Speech Detection (SSD), Instantaneous Frequency (IF)-based features either exploit Hilbert Transform (HT) or Teager-based energy separation algorithm (ESA) to estimate IF. However, HT-based approach leads to poor resolution in time-domain, and ESA-based approach leads to the lack of relative phase information. To that effect, we propose CFCCIF-QESA feature set, which encompasses excellent time resolution as well as relative phase information. Hence, we illustrate the significance of incorporating quadrature-phase component along with in-phase component for SSD of synthetic and voice converted spoof. The proposed feature set is evaluated using various performance metrics, namely, EER, MCC, F-measure, J-statistic, Jaccard Index, and Hamming loss. CFCCIF-QESA achieves a relative decrease in Average EER (AEER) by 22.53% w.r.t. the performance of CFCIF-ESA, for all the attacks in the dataset. Furthermore, results w.r.t. S10 attack (i.e., MaryTTS using unit selection synthesis), which is the most difficult to detect attack, show that CFCCIF-QESA achieves a 29.16% relative decrease in EER as compared to the CFCCIF-ESA. Furthermore, using model-level measures such as, Kullback Leibler Divergence (KLD) and Jenson Shannon Divergence (JSD), we also show the better discriminative ability of our proposed feature set CFCCIF-QESA than the existing CFCCIF-ESA. Finally, the analysis of the latency period for CFCCIF-QESA and CFCCIF-ESA is presented, and it shows better suitability of CFCCIF-QESA w.r.t. deployment in practical SSD systems.

关键词： Spoofed Speech Detection Quadrature Phase Mutual Information energy separation algorithm

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A Combined Approach to Estimate Modal Parameters for Updating the Finite Element Model of a High-Rise Building

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STRUCTURAL CONTROL & HEALTH MONITORING 2024年第1期2024卷

作者： Cai, Kang Huang, Mingfeng Wang, Chunhe Yang, Chen Ni, Yi-Qing Li, Binbin Zhejiang Univ Inst Struct Engn Coll Civil Engn & Architecture Hangzhou Peoples R China Hong Kong Polytech Univ Dept Civil & Environm Engn Hong Kong Peoples R China Guangxi Univ Sch Civil Engn & Architecture Dept Bldg Engn Nanning Peoples R China Hong Kong Branch Natl Engn Res Ctr Rail Transit El Hong Kong Branch Hong Kong Peoples R China Zhejiang Univ ZJU UIUC Inst Haining Peoples R China

Accurate estimation of modal parameters is crucial for various aspects of tall buildings, including structural design, vibration control, and state assessment. This paper first presents a combined approach for the structural modal parameter estimation by combining the empirical wavelet transform (EWT), smoothed discrete energy separation algorithm-1 (SDESA-1), and half-cycle energy operator (HCEO), referred to as EWT-SH. A numerical study on a five-story frame structure is conducted using the Newmark-beta method to validate its effectiveness and accuracy. The results demonstrate that relative errors in estimating the natural frequency and damping ratio using the EWT-SH method are significantly smaller compared to traditional methods. Furthermore, the EWT-SH method is applied to estimate the modal parameters of a real super-tall building, i.e., the SEG Plaza building in Shenzhen, using acceleration responses. Identified results confirm the applicability and accuracy of the EWT-SH method in real-world scenarios and indicate that the frequencies and damping ratios of the SEG Plaza building noticeably decrease after 20 years of service, which could partially explain the SEG building vibration event on May 18, 2021. Since the identified frequencies are quite different from those of the original finite element (FE) model of the tall building, the dual-loop particle swarm optimization (PSO) is specifically developed to update the FE model of SEG Plaza building.

关键词： damping ratio empirical wavelet transform energy separation algorithm finite element model updating natural frequency particle swarm optimization

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Effectiveness of Speech Demodulation-Based Features for Replay Detection 19

Effectiveness of Speech Demodulation-Based Features for Repl...

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19th Annual Conference of the International-Speech-Communication-Association (INTERSPEECH 2018)

作者： Kamble, Madhu R. Tak, Hemlata Patil, Hemant A. DA IICT Speech Res Lab Gandhinagar Gujarat India

ISBN: (纸本)9781510872219

Replay attack presents a great threat to Automatic Speaker Verification (ASV) system. The speech can be modeled as amplitude and frequency modulated (AM-FM) signals. In this paper, we explore speech demodulation-based features using Hilbert transform (HT) and Teager energy Operator (TEO) for replay detection. In particular, we propose features, namely, FIT-based Instantaneous Amplitude (IA) and Instantaneous Frequency (IF) Cosine Coefficients (i.e., HT-IACC and HT-IFCC) and energy separation algorithm (ESA)-based features (i.e., ESA-IACC and ESA-IFCC). For adapting instantaneous energy w.r.t given sampling frequency, ESA requires 3 samples whereas FIT requires relatively large number of samples and thus, ESA gives high time *** experiments were performed on ASV spoof 2017 Challenge database for replay spoof speech detection (SSD).The experimental results shows that ESA-based features gave lower EER. In addition, linearly spaced Gabor filterbank gave lower EER than Butterworth filterbank. To explore possible complementary information using amplitude and frequency, we have used score-level fusion of IA and IF. With HT-based feature set, the score-level fusion gave EER of 5.24 % (dev) and 10.03 % (eval), whereas ESA-based feature set reduced the EER to 2.01 % (dev) and 9.64 % (eval).

关键词： Spoofing Hilbert transform Teager energy operator energy separation algorithm

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Novel Amplitude Weighted Frequency Modulation Features for Replay Spoof Detection 11

Novel Amplitude Weighted Frequency Modulation Features for R...

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11th International Symposium on Chinese Spoken Language Processing (ISCSLP)

作者： Kamble, Madhu R. Patil, Hemant A. DA IICT Speech Res Lab Gandhinagar 382007 Gujarat India

ISBN: (纸本)9781538656273

In this paper, we propose the use of Amplitude Modulation and Frequency Modulation (AM-FM) features for replay detection task. In AM-FM signal, AM component is known to be severely affected by noise (in this case, due to replay mechanism) which is exploited in proposed feature extraction. In particular, we explore this damage in AM component to corresponding instantaneous frequency. Thus, the novelty of proposed Amplitude Weighted Frequency Cosine Coefficients (AWFCC) feature set is the use of frequency components along with weighted amplitude components that are degraded due to replay noise. The AWFCC features have the information of AM-FM and hence, gave discriminatory information in the spectral characteristics. The experiments were performed on ASVspoof 2017 Challenge database using AWFCC feature set that gave an Equal Error Rate (EER) of 6.37 % (dev) and 11.72 % (eval) set. We have compared our results with CQCC, LFCC and MFCC using Gaussian Mixture Model (GMM) classifier and found that proposed AWFCC feature set performed better than the other feature sets on both dev and eval datasets. In addition, we have used score-level fusion of CQCC and AWFCC to obtain a lower EER of 3.60 % and 11.22 % on dev and eval set.

关键词： Automatic Speaker Verification Spoofing Replay Attack energy separation algorithm Gabor Filter

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Novel Variable Length Teager energy separation Based Instantaneous Frequency Features for Replay Detection 18

Novel Variable Length Teager Energy Separation Based Instant...

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18th Annual Conference of the International-Speech-Communication-Association (INTERSPEECH 2017)

作者： Patil, Hemant A. Kamble, Madhu R. Patel, Tanvina B. Soni, Meet Dhirubhai Ambani Inst Informat & Commun Technol D Speech Res Lab Gandhinagar Gujarat India

ISBN: (纸本)9781510848764

Replay attacks presents a great risk for Automatic Speaker Verification (ASV) system. In this paper, we propose a novel replay detector based on Variable length Teager energy Operator energy separation algorithm-Instantaneous Frequency Cosine Coefficients (VESA-IFCC) for the ASV spoof 2017 challenge. The key idea here is to exploit the contribution of IF in each subband energy via ESA to capture possible changes in spectral envelope (due to transmission and channel characteristics of replay device) of replayed speech. The IF is computed from narrowband components of speech signal, and DCT is applied in IF to get proposed feature set. We compare the performance of the proposed VESA-IFCC feature set with the features developed for detecting synthetic and voice converted speech. This includes the CQCC, CFCCIF and prosody-based features. On the development set, the proposed VESA-IFCC features when fused at score-level with a variant of CFCCIF and prosody based features gave the least EER of 0.12 %. On the evaluation set, this combination gave an EER of 18.33 %. However, post-evaluation results of challenge indicate that VESA-IFCC features alone gave the relatively least EER of 14.06 % (i.e., relatively 16.11 % less compared to baseline CQCC) and hence, is a very useful countermeasure to detect replay attacks.

关键词： Automatic Speaker Verification Replay Attack Variable length Teager energy Operator energy separation algorithm Instantaneous Frequency Cosine Coefficients

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Novel energy separation Based Instantaneous Frequency Features for Spoof Speech Detection 25

Novel Energy Separation Based Instantaneous Frequency Featur...

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25th European Signal Processing Conference (EUSIPCO)

作者： Kamble, Madhu R. Patil, Hemant A. DA IICT Gandhinagar 382007 Gujarat India

ISBN: (纸本)9780992862671

Speech Synthesis (SS) and Voice Conversion (VC) presents a genuine risk of attacks for Automatic Speaker Verification (ASV) technology. In this paper, we evaluate front-end anti-spoofing technique to protect ASV system for SS and VC attack using a standard benchmarking database. In particular, we propose a novel feature set, namely, energy separation algorithm-based Instantaneous Frequency Cosine Coefficients (ESA-IFCC) to detect the genuine and impostor speech. The experiments are carried out on ASV Spoof 2015 Challenge database. On the development set, the score-level fusion of proposed ESA-IFCC feature set with Mel Frequency Cepstral Coefficients (MFCC) gave an EER of 3.45 %, which reduced significantly from MFCC (6.98 %) and ESA-IFCC (5.43 %) with 13-D static features. The EER decreases further to 2.01 % and 1.89 % for Delta and Delta Delta features derived from proposed ESAIFCC features, respectively. The overall average error rate for known and unknown attacks in evaluation set was 6.79 % for ESA-IFCC and was significantly better than the MFCC (9.15 %) features.

关键词： Teager energy Operator energy separation algorithm Instantaneous Frequency Cosine Coefficients SSD GMM EER

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