Voice Cloning

Papers

• VQMIVC: Vector Quantization And Mutual Information-based Unsupervised Speech Representation Disentanglement For One-shot Voice Conversion (2021)
  Disong Wang, Liqun Deng, Yu Ting Yeung, et al.
  20.31
• A Comparison Of Discrete And Soft Speech Units For Improved Voice Conversion (2021)
  Benjamin van Niekerk, Marc-André Carbonneau, Julian Zaïdi, et al.
  20.25
• An Overview Of Voice Conversion And Its Challenges: From Statistical Modeling To Deep Learning (2020)
  Berrak Sisman, Junichi Yamagishi, Simon King, et al.
  18.53
• Cyclegan-vc2: Improved Cyclegan-based Non-parallel Voice Conversion (2019)
  Takuhiro Kaneko, Hirokazu Kameoka, Kou Tanaka, et al.
  17.45
• One-class Learning Towards Synthetic Voice Spoofing Detection (2020)
  You Zhang, Fei Jiang, Zhiyao Duan
  17.31
• The Voice Conversion Challenge 2018: Promoting Development Of Parallel And Nonparallel Methods (2018)
  Jaime Lorenzo-Trueba, Junichi Yamagishi, Tomoki Toda, et al.
  17.06
• Mosnet: Deep Learning Based Objective Assessment For Voice Conversion (2019)
  Chen-Chou Lo, Szu-Wei Fu, Wen-Chin Huang, et al.
  16.90
• Voice Conversion From Unaligned Corpora Using Variational Autoencoding Wasserstein Generative Adversarial Networks (2017)
  Chin-Cheng Hsu, Hsin-Te Hwang, Yi-Chiao Wu, et al.
  16.34
• Seen And Unseen Emotional Style Transfer For Voice Conversion With A New Emotional Speech Dataset (2020)
  Kun Zhou, Berrak Sisman, Rui Liu, et al.
  16.34
• Emotional Voice Conversion: Theory, Databases And ESD (2021)
  Kun Zhou, Berrak Sisman, Rui Liu, et al.
  16.30
• Learning To Speak Fluently In A Foreign Language: Multilingual Speech Synthesis And Cross-language Voice Cloning (2019)
  Yu Zhang, Ron J. Weiss, Heiga Zen, et al.
  15.03
• Sequence-to-sequence Acoustic Modeling For Voice Conversion (2018)
  Jing-Xuan Zhang, Zhen-Hua Ling, Li-Juan Liu, et al.
  14.97
• ACVAE-VC: Non-parallel Many-to-many Voice Conversion With Auxiliary Classifier Variational Autoencoder (2018)
  Hirokazu Kameoka, Takuhiro Kaneko, Kou Tanaka, et al.
  14.69
• AGAIN-VC: A One-shot Voice Conversion Using Activation Guidance And Adaptive Instance Normalization (2020)
  Yen-Hao Chen, da-Yi Wu, Tsung-Han Wu, et al.
  14.27
• Any-to-many Voice Conversion With Location-relative Sequence-to-sequence Modeling (2020)
  Songxiang Liu, Yuewen Cao, Disong Wang, et al.
  14.02
• Non-parallel Sequence-to-sequence Voice Conversion With Disentangled Linguistic And Speaker Representations (2019)
  Jing-Xuan Zhang, Zhen-Hua Ling, Li-Rong Dai
  14.02
• Starganv2-vc: A Diverse, Unsupervised, Non-parallel Framework For Natural-sounding Voice Conversion (2021)
  Yinghao Aaron Li, Ali Zare, Nima Mesgarani
  13.70
• Multi-target Voice Conversion Without Parallel Data By Adversarially Learning Disentangled Audio Representations (2018)
  Ju-Chieh Chou, Cheng-Chieh Yeh, Hung-Yi Lee, et al.
  13.60
• Voice Activity Detection: Merging Source And Filter-based Information (2019)
  Thomas Drugman, Yannis Stylianou, Yusuke Kida, et al.
  13.50
• VQVC+: One-shot Voice Conversion By Vector Quantization And U-net Architecture (2020)
  da-Yi Wu, Yen-Hao Chen, Hung-Yi Lee
  13.34
• Voice Impersonation Using Generative Adversarial Networks (2018)
  Yang Gao, Rita Singh, Bhiksha Raj
  13.23
• Voice Transformer Network: Sequence-to-sequence Voice Conversion Using Transformer With Text-to-speech Pretraining (2019)
  Wen-Chin Huang, Tomoki Hayashi, Yi-Chiao Wu, et al.
  13.17
• F0-consistent Many-to-many Non-parallel Voice Conversion Via Conditional Autoencoder (2020)
  Kaizhi Qian, Zeyu Jin, Mark Hasegawa-Johnson, et al.
  13.17
• Transfer Learning From Speech Synthesis To Voice Conversion With Non-parallel Training Data (2020)
  Mingyang Zhang, Yi Zhou, Li Zhao, et al.
  12.74
• Voice Conversion Challenge 2020: Intra-lingual Semi-parallel And Cross-lingual Voice Conversion (2020)
  Yi Zhao, Wen-Chin Huang, Xiaohai Tian, et al.
  12.74
• Convs2s-vc: Fully Convolutional Sequence-to-sequence Voice Conversion (2018)
  Hirokazu Kameoka, Kou Tanaka, Damian Kwasny, et al.
  12.68
• Fragmentvc: Any-to-any Voice Conversion By End-to-end Extracting And Fusing Fine-grained Voice Fragments With Attention (2020)
  Yist Y. Lin, Chung-Ming Chien, Jheng-Hao Lin, et al.
  12.54
• Transforming Spectrum And Prosody For Emotional Voice Conversion With Non-parallel Training Data (2020)
  Kun Zhou, Berrak Sisman, Haizhou Li
  12.54
• AVQVC: One-shot Voice Conversion By Vector Quantization With Applying Contrastive Learning (2022)
  Huaizhen Tang, Xulong Zhang, Jianzong Wang, et al.
  12.40
• S2VC: A Framework For Any-to-any Voice Conversion With Self-supervised Pretrained Representations (2021)
  Jheng-Hao Lin, Yist Y. Lin, Chung-Ming Chien, et al.
  12.25
• Can We Steal Your Vocal Identity From The Internet?: Initial Investigation Of Cloning Obama's Voice Using GAN, Wavenet And Low-quality Found Data (2018)
  Jaime Lorenzo-Trueba, Fuming Fang, Xin Wang, et al.
  12.02
• Investigating On Incorporating Pretrained And Learnable Speaker Representations For Multi-speaker Multi-style Text-to-speech (2021)
  Chung-Ming Chien, Jheng-Hao Lin, Chien-Yu Huang, et al.
  11.67
• Assem-vc: Realistic Voice Conversion By Assembling Modern Speech Synthesis Techniques (2021)
  Kang-Wook Kim, Seung-Won Park, Junhyeok Lee, et al.
  11.64
• Cotatron: Transcription-guided Speech Encoder For Any-to-many Voice Conversion Without Parallel Data (2020)
  Seung-Won Park, Doo-Young Kim, Myun-Chul Joe
  11.49
• People Are Poorly Equipped To Detect Ai-powered Voice Clones (2024)
  Sarah Barrington, Emily A. Cooper, Hany Farid
  11.39
• Voice Conversion Using Sequence-to-sequence Learning Of Context Posterior Probabilities (2017)
  Hiroyuki Miyoshi, Yuki Saito, Shinnosuke Takamichi, et al.
  11.39
• Converting Anyone's Emotion: Towards Speaker-independent Emotional Voice Conversion (2020)
  Kun Zhou, Berrak Sisman, Mingyang Zhang, et al.
  11.39
• DDDM-VC: Decoupled Denoising Diffusion Models With Disentangled Representation And Prior Mixup For Verified Robust Voice Conversion (2023)
  Ha-Yeong Choi, Sang-Hoon Lee, Seong-Whan Lee
  11.29
• Voice Conversion Based On Cross-domain Features Using Variational Auto Encoders (2018)
  Wen-Chin Huang, Hsin-Te Hwang, Yu-Huai Peng, et al.
  11.29
• Unsupervised Singing Voice Conversion (2019)
  Eliya Nachmani, Lior Wolf
  11.19
• Wgansing: A Multi-voice Singing Voice Synthesizer Based On The Wasserstein-gan (2019)
  Pritish Chandna, Merlijn Blaauw, Jordi Bonada, et al.
  11.08
• Speech Representation Disentanglement With Adversarial Mutual Information Learning For One-shot Voice Conversion (2022)
  Sicheng Yang, Methawee Tantrawenith, Haolin Zhuang, et al.
  11.08
• Pitchnet: Unsupervised Singing Voice Conversion With Pitch Adversarial Network (2019)
  Chengqi Deng, Chengzhu Yu, Heng Lu, et al.
  10.97
• Disentanglement Of Emotional Style And Speaker Identity For Expressive Voice Conversion (2021)
  Zongyang Du, Berrak Sisman, Kun Zhou, et al.
  10.97
• S3PRL-VC: Open-source Voice Conversion Framework With Self-supervised Speech Representations (2021)
  Wen-Chin Huang, Shu-Wen Yang, Tomoki Hayashi, et al.
  10.97
• Robust Disentangled Variational Speech Representation Learning For Zero-shot Voice Conversion (2022)
  Jiachen Lian, Chunlei Zhang, Dong Yu
  10.97
• Many-to-many Voice Conversion Using Conditional Cycle-consistent Adversarial Networks (2020)
  Shindong Lee, Bonggu Ko, Keonnyeong Lee, et al.
  10.85
• An Adaptive Learning Based Generative Adversarial Network For One-to-one Voice Conversion (2021)
  Sandipan Dhar, Nanda Dulal Jana, Swagatam Das
  10.61
• The Voiceprivacy 2022 Challenge: Progress And Perspectives In Voice Anonymisation (2024)
  Michele Panariello, Natalia Tomashenko, Xin Wang, et al.
  10.61
• Disentangleing Content And Fine-grained Prosody Information Via Hybrid ASR Bottleneck Features For Voice Conversion (2022)
  Xintao Zhao, Feng Liu, Changhe Song, et al.
  10.48