SOTAVerified

Voice Conversion

I remember all the summer days Drinking wine in the sunshine I hope it never leaves And I remember all the summer nights Staring at you in the moonlight I hope you never leave 'cause baby You're so good to me You have all that all that I ever need It's easy to love you So easy to love you Ooh you know it's true The best part of being with you To know you're with me It's not so hard to say It's easy to love you I remember all those winter days frozen In the cold tryin' to get you home Should I be moving in, we can be together then Remember spending all those winter nights Stayin' inside by the warm fire Yeah you gotta know that I can never let you go You and I have the rest of our lives to say It's easy to love you So easy to love you Ooh you know it's true The best part of being with you To know you're with me It's not so hard to say It's easy to love you Can anybody else see it? Mm, can anybody else see what I do? Can anybody else feel it? Oh, can anybody else feel the way I do? But now I'm with you Hard to forget all the moments when We'd be sitting there hoping it would never end 'Cause this is meant to be So baby, will you marry me? It's easy to love you So easy to love you Ooh, you know it's true The best part of being with you To know you are with me It's not so hard to say It's easy to love you You and me will be together I know our love will last forever You and me will be together I know our love will last forever You know it's true The best part of being with you You're easy to love

Source: Joint training framework for text-to-speech and voice conversion using multi-source Tacotron and WaveNet

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 301–350 of 520 papers

TitleStatusHype
以線性多變量迴歸來對映分段後音框之語音轉換方法 (A Voice Conversion Method Mapping Segmented Frames with Linear Multivariate Regression) [In Chinese]—0
Axial Residual Networks for CycleGAN-based Voice Conversion—0
Beyond Voice Identity Conversion: Manipulating Voice Attributes by Adversarial Learning of Structured Disentangled Representations—0
Boosting Star-GANs for Voice Conversion with Contrastive Discriminator—0
Bootstrapping non-parallel voice conversion from speaker-adaptive text-to-speech—0
Building Synthetic Voices in the META-NET Framework—0
Can we steal your vocal identity from the Internet?: Initial investigation of cloning Obama's voice using GAN, WaveNet and low-quality found data—0
Catch You and I Can: Revealing Source Voiceprint Against Voice Conversion—0
Change your singer: a transfer learning generative adversarial framework for song to song conversion—0
ClapFM-EVC: High-Fidelity and Flexible Emotional Voice Conversion with Dual Control from Natural Language and Speech—0
ClsVC: Learning Speech Representations with two different classification tasks.—0
Collective Learning Mechanism based Optimal Transport Generative Adversarial Network for Non-parallel Voice Conversion—0
Combining Automatic Speaker Verification and Prosody Analysis for Synthetic Speech Detection—0
Comparison of Speech Representations for the MOS Prediction System—0
Conditional Deep Hierarchical Variational Autoencoder for Voice Conversion—0
Converting Anyone's Voice: End-to-End Expressive Voice Conversion with a Conditional Diffusion Model—0
ConvS2S-VC: Fully convolutional sequence-to-sequence voice conversion—0
CO-VADA: A Confidence-Oriented Voice Augmentation Debiasing Approach for Fair Speech Emotion Recognition—0
Learning Speech Representation From Contrastive Token-Acoustic Pretraining—0
Creating New Voices using Normalizing Flows—0
Creating Personalized Synthetic Voices from Post-Glossectomy Speech with Guided Diffusion Models—0
Cross-lingual Knowledge Distillation via Flow-based Voice Conversion for Robust Polyglot Text-To-Speech—0
Cross-lingual Text-To-Speech with Flow-based Voice Conversion for Improved Pronunciation—0
Cross-modal Face- and Voice-style Transfer—0
Crossmodal Voice Conversion—0
Cross-Speaker Emotion Transfer for Low-Resource Text-to-Speech Using Non-Parallel Voice Conversion with Pitch-Shift Data Augmentation—0
Cross-speaker style transfer for text-to-speech using data augmentation—0
CTEFM-VC: Zero-Shot Voice Conversion Based on Content-Aware Timbre Ensemble Modeling and Flow Matching—0
Custom Data Augmentation for low resource ASR using Bark and Retrieval-Based Voice Conversion—0
CycleFlow: Purify Information Factors by Cycle Loss—0
Data Augmentation for Diverse Voice Conversion in Noisy Environments—0
D-CAPTCHA++: A Study of Resilience of Deepfake CAPTCHA under Transferable Imperceptible Adversarial Attack—0
DeepA: A Deep Neural Analyzer For Speech And Singing Vocoding—0
Deep Learning-based F0 Synthesis for Speaker Anonymization—0
Deep MOS Predictor for Synthetic Speech Using Cluster-Based Modeling—0
DeepSonar: Towards Effective and Robust Detection of AI-Synthesized Fake Voices—0
Delivering Speaking Style in Low-resource Voice Conversion with Multi-factor Constraints—0
Dictionary Update for NMF-based Voice Conversion Using an Encoder-Decoder Network—0
Differentiable WORLD Synthesizer-based Neural Vocoder With Application To End-To-End Audio Style Transfer—0
ZSDEVC: Zero-Shot Diffusion-based Emotional Voice Conversion with Disentangled Mechanism—0
DiffSVC: A Diffusion Probabilistic Model for Singing Voice Conversion—0
Discl-VC: Disentangled Discrete Tokens and In-Context Learning for Controllable Zero-Shot Voice Conversion—0
Discrete Optimal Transport and Voice Conversion—0
Discrete Unit based Masking for Improving Disentanglement in Voice Conversion—0
DisC-VC: Disentangled and F0-Controllable Neural Voice Conversion—0
Disentangled Feature Learning for Real-Time Neural Speech Coding—0
Disentangled Speech Representation Learning Based on Factorized Hierarchical Variational Autoencoder with Self-Supervised Objective—0
Disentangled Speech Representation Learning for One-Shot Cross-lingual Voice Conversion Using β-VAE—0
Disentangleing Content and Fine-grained Prosody Information via Hybrid ASR Bottleneck Features for Voice Conversion—0
Disentangling Prosody Representations with Unsupervised Speech Reconstruction—0
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All datasetsZeroSpeech 2019 EnglishLibriSpeech test-cleanVCTK

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1VQ-CPCSpeaker Similarity3.8—Unverified
2VQ-VAESpeaker Similarity3.49—Unverified
#ModelMetricClaimedVerifiedStatus
1kNN-VC (prematched HiFiGAN)Character Error Rate (CER)2.96—Unverified
#ModelMetricClaimedVerifiedStatus
1DISSCTotal Length Error (TLE)0.83—Unverified