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

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Showing 51–100 of 520 papers

TitleStatusHype
Low-Latency Real-Time Non-Parallel Voice Conversion based on Cyclic Variational Autoencoder and Multiband WaveRNN with Data-Driven Linear PredictionCode1
Assem-VC: Realistic Voice Conversion by Assembling Modern Speech Synthesis TechniquesCode1
S2VC: A Framework for Any-to-Any Voice Conversion with Self-Supervised Pretrained RepresentationsCode1
Rhythm Modeling for Voice ConversionCode1
FMFCC-A: A Challenging Mandarin Dataset for Synthetic Speech DetectionCode1
Spectrogram-channels u-net: a source separation model viewing each channel as the spectrogram of each sourceCode1
Robust Disentangled Variational Speech Representation Learning for Zero-shot Voice ConversionCode1
MOSNet: Deep Learning based Objective Assessment for Voice ConversionCode1
Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised RepresentationsCode1
Nonparallel Voice Conversion with Augmented Classifier Star Generative Adversarial NetworksCode1
End-to-End Zero-Shot Voice Conversion with Location-Variable ConvolutionsCode1
Non-Parallel Voice Conversion with Cyclic Variational AutoencoderCode1
Emotionless: Privacy-Preserving Speech Analysis for Voice AssistantsCode1
F0-consistent many-to-many non-parallel voice conversion via conditional autoencoderCode1
HM-Conformer: A Conformer-based audio deepfake detection system with hierarchical pooling and multi-level classification token aggregation methodsCode1
Robust Training of Vector Quantized Bottleneck ModelsCode1
Efficient Non-Autoregressive GAN Voice Conversion using VQWav2vec Features and Dynamic ConvolutionCode1
Disentanglement in a GAN for Unconditional Speech SynthesisCode1
Pretraining Techniques for Sequence-to-Sequence Voice ConversionCode1
DeID-VC: Speaker De-identification via Zero-shot Pseudo Voice ConversionCode1
Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling SchemeCode1
BiSinger: Bilingual Singing Voice SynthesisCode1
A Comparative Study of Self-supervised Speech Representation Based Voice ConversionCode1
Defending Your Voice: Adversarial Attack on Voice ConversionCode1
Building Bilingual and Code-Switched Voice Conversion with Limited Training Data Using Embedding Consistency LossCode1
Any-to-Many Voice Conversion with Location-Relative Sequence-to-Sequence ModelingCode1
DuTa-VC: A Duration-aware Typical-to-atypical Voice Conversion Approach with Diffusion Probabilistic ModelCode1
Emo-StarGAN: A Semi-Supervised Any-to-Many Non-Parallel Emotion-Preserving Voice ConversionCode1
Region-Based Optimization in Continual Learning for Audio Deepfake DetectionCode1
CinC-GAN for Effective F0 prediction for Whisper-to-Normal Speech ConversionCode1
Deep Learning Based Assessment of Synthetic Speech NaturalnessCode1
Evaluating Methods for Ground-Truth-Free Foreign Accent ConversionCode1
FastSVC: Fast Cross-Domain Singing Voice Conversion with Feature-wise Linear ModulationCode1
Baseline System of Voice Conversion Challenge 2020 with Cyclic Variational Autoencoder and Parallel WaveGANCode1
CycleTransGAN-EVC: A CycleGAN-based Emotional Voice Conversion Model with TransformerCode1
FragmentVC: Any-to-Any Voice Conversion by End-to-End Extracting and Fusing Fine-Grained Voice Fragments With AttentionCode1
Anonymizing Speech: Evaluating and Designing Speaker Anonymization TechniquesCode1
FSD: An Initial Chinese Dataset for Fake Song DetectionCode1
AutoVisual Fusion Suite: A Comprehensive Evaluation of Image Segmentation and Voice Conversion Tools on HuggingFace PlatformCode1
ControlVC: Zero-Shot Voice Conversion with Time-Varying Controls on Pitch and SpeedCode1
Converting Anyone's Emotion: Towards Speaker-Independent Emotional Voice ConversionCode1
AraBERT: Transformer-based Model for Arabic Language UnderstandingCode1
CycleGAN-VC3: Examining and Improving CycleGAN-VCs for Mel-spectrogram ConversionCode1
Emotional Voice Conversion: Theory, Databases and ESDCode1
Accurate Emotion Strength Assessment for Seen and Unseen Speech Based on Data-Driven Deep LearningCode1
Improving fairness for spoken language understanding in atypical speech with Text-to-SpeechCode1
Blow: a single-scale hyperconditioned flow for non-parallel raw-audio voice conversionCode1
crank: An Open-Source Software for Nonparallel Voice Conversion Based on Vector-Quantized Variational AutoencoderCode1
A unified one-shot prosody and speaker conversion system with self-supervised discrete speech unitsCode1
CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal ConversionCode1
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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