A Replay Voice Detection Algorithm Based on Multi-feature Fusion

Lin, Lang; Wang, Rangding; Yan, Diqun; Li, Can

doi:10.1007/978-3-030-00021-9_27

Cited by 2 publications

(3 citation statements)

References 10 publications

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“…In our previous research on ASVspoof 2017 dataset, we performed a detailed analysis of the differences between genuine speech and the replay speech on the frequency sub-bands. Our research showed that the discriminative information of genuine speech and replay speech is mainly distributed in two sub-bands, i.e., 0-1 kHz and 7-8 kHz [12] [13]. one plausible explanation for this observation can be as follows.…”

Section: Introductionmentioning

confidence: 67%

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A Robust Method for Speech Replay Attack Detection

2020

KSII TIIS

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Spoofing attacks, especially replay attacks, pose great security challenges to automatic speaker verification (ASV) systems. Current works on replay attacks detection primarily focused on either developing new features or improving classifier performance, ignoring the effects of feature variability, e.g., the channel variability. In this paper, we first establish a mathematical model for replay speech and introduce a method for eliminating the negative interference of the channel. Then a novel feature is proposed to detect the replay attacks. To further boost the detection performance, four post-processing methods using normalization techniques are investigated. We evaluate our proposed method on the ASVspoof 2017 dataset. The experimental results show that our approach outperforms the competing methods in terms of detection accuracy. More interestingly, we find that the proposed normalization strategy could also improve the performance of the existing algorithms.

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Section: Introductionmentioning

confidence: 67%

“…In our preliminary studies [12][13], we found that the spoofing information is mainly distributed in the low-frequency region (0-1kHz) and the high-frequency region (7-8 kHz) of the spectrum. Therefore, the SFCC feature proposed in this paper is based on these two discriminative sub-bands.…”

Section: Feature Extractionmentioning

confidence: 99%

A Robust Method for Speech Replay Attack Detection

2020

KSII TIIS

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“… The color feature-based methods : Stain defects on the surface of industrial products can cause color jumps. The color feature-based methods mainly uses color histograms ( Prasitmeeboon & Yau, 2019 ) to describe the proportion of different colors in an image or color moments ( Li, Quan & Wang, 2020 ) to describe the distribution of colors to accomplish anomaly detection. …”

Section: Related Workmentioning

confidence: 99%

Adaptive visual detection of industrial product defects

Zhang

Wang

Chen

et al. 2023

PeerJ Computer Science

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Visual inspection of the appearance defects on industrial products has always been a research hotspot pursued by industry and academia. Due to the lack of samples in the industrial defect dataset and the serious class imbalance, deep learning technology cannot be directly applied to industrial defect visual inspection to meet the real application needs. Transfer learning is a good choice to deal with insufficient samples. However, cross-dataset bias is unavoidable during simple knowledge transfer. We noticed that the appearance defects of industrial products are similar, and most defects can be classified as stains or texture jumps, which provides a research basis for building a universal and adaptive industrial defect detection model. In this article, based on the idea of model-agnostic meta-learning (MAML), we propose an adaptive industrial defect detection model through learning from multiple known industrial defect datasets and then transfer it to the novel anomaly detection tasks. In addition, the Siamese network is used to extract differential features to minimize the influence of defect types on model generalization, and can also highlight defect features and improve model detection performance. At the same time, we add a coordinate attention mechanism to the model, which realizes the feature enhancement of the region of interest in terms of two coordinate dimensions. In the simulation experiments, we construct and publish a visual defect dataset of injection molded bottle cups, termed BC defects, which can complement existing industrial defect visual data benchmarks. Simulation results based on BC defects dataset and other public datasets have demonstrated the effectiveness of the proposed general visual detection model for industrial defects. The dataset and code are available at https://github.com/zhg-SZPT/MeDetection.

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A Replay Voice Detection Algorithm Based on Multi-feature Fusion

Cited by 2 publications

References 10 publications

A Robust Method for Speech Replay Attack Detection

A Robust Method for Speech Replay Attack Detection

Adaptive visual detection of industrial product defects

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