How Deep Are the Fakes? Focusing on Audio Deepfake: A Survey
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Vandana P. Janeja | Zahra Khanjani | Gabrielle Watson | V. Janeja | Zahra Khanjani | Gabrielle Watson | V. P Janeja
[1] Chi-Man Pun,et al. Audio Replay Spoof Attack Detection Using Segment-based Hybrid Feature and DenseNet-LSTM Network , 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[2] Yoshua Bengio,et al. MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis , 2019, NeurIPS.
[3] Alexei A. Efros,et al. Image-to-Image Translation with Conditional Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[4] Kou Tanaka,et al. StarGAN-VC: non-parallel many-to-many Voice Conversion Using Star Generative Adversarial Networks , 2018, 2018 IEEE Spoken Language Technology Workshop (SLT).
[5] Aythami Morales,et al. DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection , 2020, Inf. Fusion.
[6] Junichi Yamagishi,et al. High-Quality Nonparallel Voice Conversion Based on Cycle-Consistent Adversarial Network , 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[7] Gautham J. Mysore,et al. VoCo , 2017, ACM Trans. Graph..
[8] Zhifeng Xie,et al. ResNet and Model Fusion for Automatic Spoofing Detection , 2017, INTERSPEECH.
[9] Jaakko Lehtinen,et al. Analyzing and Improving the Image Quality of StyleGAN , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Mahdieh Soleymani Baghshah,et al. DGSAN: Discrete Generative Self-Adversarial Network , 2019, Neurocomputing.
[11] Mike Lewis,et al. MelNet: A Generative Model for Audio in the Frequency Domain , 2019, ArXiv.
[12] Eduardo Lleida,et al. Preventing replay attacks on speaker verification systems , 2011, 2011 Carnahan Conference on Security Technology.
[13] Saeid Nahavandi,et al. Deep learning for deepfakes creation and detection: A survey , 2019, Comput. Vis. Image Underst..
[14] Vimal Kumar,et al. Combating Deepfakes: Multi-LSTM and Blockchain as Proof of Authenticity for Digital Media , 2020, 2020 IEEE / ITU International Conference on Artificial Intelligence for Good (AI4G).
[15] Chi-Man Pun,et al. Audio Replay Spoof Attack Detection by Joint Segment-Based Linear Filter Bank Feature Extraction and Attention-Enhanced DenseNet-BiLSTM Network , 2020, IEEE/ACM Transactions on Audio, Speech, and Language Processing.
[16] Mani B. Srivastava,et al. Deep Residual Neural Networks for Audio Spoofing Detection , 2019, INTERSPEECH.
[17] Nandakumar Paramparambath,et al. Audio Spoofing Verification using Deep Convolutional Neural Networks by Transfer Learning , 2020, ArXiv.
[18] Tiago M. Fernández-Caramés,et al. Fake News, Disinformation, and Deepfakes: Leveraging Distributed Ledger Technologies and Blockchain to Combat Digital Deception and Counterfeit Reality , 2019, IT Professional.
[19] Joaquín González-Rodríguez,et al. An Audio Fingerprinting Approach to Replay Attack Detection on ASVSPOOF 2017 Challenge Data , 2018, Odyssey.
[20] Victor Lempitsky,et al. Few-Shot Adversarial Learning of Realistic Neural Talking Head Models , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[21] Yoshinori Sagisaka,et al. Speech spectrum conversion based on speaker interpolation and multi-functional representation with weighting by radial basis function networks , 1995, Speech Commun..
[22] Sanjeev Khudanpur,et al. Librispeech: An ASR corpus based on public domain audio books , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[23] Simon Lui,et al. Toward Robust Audio Spoofing Detection: A Detailed Comparison of Traditional and Learned Features , 2019, IEEE Access.
[24] Li-Rong Dai,et al. Non-Parallel Sequence-to-Sequence Voice Conversion With Disentangled Linguistic and Speaker Representations , 2019, IEEE/ACM Transactions on Audio, Speech, and Language Processing.
[25] Haizhou Li,et al. SINGAN: Singing Voice Conversion with Generative Adversarial Networks , 2019, 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC).
[26] Chuan Li,et al. Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[27] Yang Yang,et al. FGGAN: Feature-Guiding Generative Adversarial Networks for Text Generation , 2020, IEEE Access.
[28] Sercan Ömer Arik,et al. Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning , 2017, ICLR.
[29] Shao-Liang Chang,et al. A Trusting News Ecosystem Against Fake News from Humanity and Technology Perspectives , 2019, 2019 19th International Conference on Computational Science and Its Applications (ICCSA).
[30] Heiga Zen,et al. WaveNet: A Generative Model for Raw Audio , 2016, SSW.
[31] Timo Aila,et al. A Style-Based Generator Architecture for Generative Adversarial Networks , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Liang Zhang,et al. Deep Learning in Face Synthesis: A Survey on Deepfakes , 2020, 2020 IEEE 3rd International Conference on Computer and Communication Engineering Technology (CCET).
[33] Simone Scardapane,et al. On the use of deep recurrent neural networks for detecting audio spoofing attacks , 2017, 2017 International Joint Conference on Neural Networks (IJCNN).
[34] Jaehyeon Kim,et al. HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis , 2020, NeurIPS.
[35] Sercan Ömer Arik,et al. Deep Voice 2: Multi-Speaker Neural Text-to-Speech , 2017, NIPS.
[36] Galina Lavrentyeva,et al. Audio Replay Attack Detection with Deep Learning Frameworks , 2017, INTERSPEECH.
[37] Joon Son Chung,et al. VoxCeleb2: Deep Speaker Recognition , 2018, INTERSPEECH.
[38] Qingyang Wu,et al. TextGAIL: Generative Adversarial Imitation Learning for Text Generation , 2020, AAAI.
[39] Yang Gao,et al. Voice Impersonation Using Generative Adversarial Networks , 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[40] Wei Sun,et al. Combating Replay Attacks Against Voice Assistants , 2019, Proc. ACM Interact. Mob. Wearable Ubiquitous Technol..
[41] Saniat Javid Sohrawardi,et al. Recurrent Convolutional Structures for Audio Spoof and Video Deepfake Detection , 2020, IEEE Journal of Selected Topics in Signal Processing.
[42] Thomas Fang Zheng,et al. A Study on Replay Attack and Anti-Spoofing for Automatic Speaker Verification , 2017, INTERSPEECH.
[43] Patrick Nguyen,et al. Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis , 2018, NeurIPS.
[44] João Paulo Papa,et al. A survey on text generation using generative adversarial networks , 2021, Pattern Recognit..
[45] Dinesh Manocha,et al. Emotions Don't Lie: An Audio-Visual Deepfake Detection Method using Affective Cues , 2020, ACM Multimedia.
[46] R. Parizi,et al. Making Sense of Blockchain for AI Deepfakes Technology , 2020, 2020 IEEE Globecom Workshops (GC Wkshps.
[47] Tomoki Toda,et al. Voice Conversion Based on Maximum-Likelihood Estimation of Spectral Parameter Trajectory , 2007, IEEE Transactions on Audio, Speech, and Language Processing.
[48] Adam Coates,et al. Deep Voice: Real-time Neural Text-to-Speech , 2017, ICML.
[49] Ryan Prenger,et al. Waveglow: A Flow-based Generative Network for Speech Synthesis , 2018, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[50] Simon King,et al. Attentive Filtering Networks for Audio Replay Attack Detection , 2018, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[51] Xiangui Kang,et al. A Capsule Network Based Approach for Detection of Audio Spoofing Attacks , 2021, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[52] Jakub Galka,et al. Audio Replay Attack Detection Using High-Frequency Features , 2017, INTERSPEECH.
[53] Navdeep Jaitly,et al. Natural TTS Synthesis by Conditioning Wavenet on MEL Spectrogram Predictions , 2017, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[54] Kong-Aik Lee,et al. The ASVspoof 2017 Challenge: Assessing the Limits of Replay Spoofing Attack Detection , 2017, INTERSPEECH.
[55] Prasenjit Dey,et al. End-To-End Audio Replay Attack Detection Using Deep Convolutional Networks with Attention , 2018, INTERSPEECH.
[56] Alexei A. Efros,et al. Everybody Dance Now , 2018, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[57] Ganesh Sivaraman,et al. Generalization of Audio Deepfake Detection , 2020, Odyssey.
[58] Jacek Naruniec,et al. High‐Resolution Neural Face Swapping for Visual Effects , 2020, Comput. Graph. Forum.
[59] Xiongwei Zhang,et al. Attention-Based LSTM Algorithm for Audio Replay Detection in Noisy Environments , 2019 .
[60] Zhiyao Duan,et al. One-Class Learning Towards Synthetic Voice Spoofing Detection , 2020, IEEE Signal Processing Letters.
[61] Jason Lee,et al. Fully Character-Level Neural Machine Translation without Explicit Segmentation , 2016, TACL.
[62] Shinnosuke Takamichi,et al. Statistical Parametric Speech Synthesis Incorporating Generative Adversarial Networks , 2017, IEEE/ACM Transactions on Audio, Speech, and Language Processing.
[63] Felix Juefei-Xu,et al. FakeSpotter: A Simple yet Robust Baseline for Spotting AI-Synthesized Fake Faces , 2019, IJCAI.
[64] Bayya Yegnanarayana,et al. Transformation of formants for voice conversion using artificial neural networks , 1995, Speech Commun..
[65] Yisroel Mirsky,et al. The Creation and Detection of Deepfakes , 2020, ACM Comput. Surv..