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 101–150 of 520 papers

TitleStatusHype
Baseline System of Voice Conversion Challenge 2020 with Cyclic Variational Autoencoder and Parallel WaveGANCode1
Transfer Learning from Monolingual ASR to Transcription-free Cross-lingual Voice ConversionCode1
Any-to-Many Voice Conversion with Location-Relative Sequence-to-Sequence ModelingCode1
Nonparallel Voice Conversion with Augmented Classifier Star Generative Adversarial NetworksCode1
CinC-GAN for Effective F0 prediction for Whisper-to-Normal Speech ConversionCode1
Pretraining Techniques for Sequence-to-Sequence Voice ConversionCode1
VQVC+: One-Shot Voice Conversion by Vector Quantization and U-Net architectureCode1
Vector-quantized neural networks for acoustic unit discovery in the ZeroSpeech 2020 challengeCode1
Defending Your Voice: Adversarial Attack on Voice ConversionCode1
Robust Training of Vector Quantized Bottleneck ModelsCode1
Converting Anyone's Emotion: Towards Speaker-Independent Emotional Voice ConversionCode1
F0-consistent many-to-many non-parallel voice conversion via conditional autoencoderCode1
AraBERT: Transformer-based Model for Arabic Language UnderstandingCode1
Transforming Spectrum and Prosody for Emotional Voice Conversion with Non-Parallel Training DataCode1
Unsupervised Representation Disentanglement using Cross Domain Features and Adversarial Learning in Variational Autoencoder based Voice ConversionCode1
Voice Transformer Network: Sequence-to-Sequence Voice Conversion Using Transformer with Text-to-Speech PretrainingCode1
Emotionless: Privacy-Preserving Speech Analysis for Voice AssistantsCode1
Non-Parallel Voice Conversion with Cyclic Variational AutoencoderCode1
Blow: a single-scale hyperconditioned flow for non-parallel raw-audio voice conversionCode1
Investigation of F0 conditioning and Fully Convolutional Networks in Variational Autoencoder based Voice ConversionCode1
MOSNet: Deep Learning based Objective Assessment for Voice ConversionCode1
One-shot Voice Conversion by Separating Speaker and Content Representations with Instance NormalizationCode1
Spectrogram-channels u-net: a source separation model viewing each channel as the spectrogram of each sourceCode1
Voice Conversion Based on Cross-Domain Features Using Variational Auto EncodersCode1
StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networksCode1
RT-VC: Real-Time Zero-Shot Voice Conversion with Speech Articulatory Coding—0
CO-VADA: A Confidence-Oriented Voice Augmentation Debiasing Approach for Fair Speech Emotion Recognition—0
Towards Better Disentanglement in Non-Autoregressive Zero-Shot Expressive Voice Conversion—0
StarVC: A Unified Auto-Regressive Framework for Joint Text and Speech Generation in Voice Conversion—0
Unsupervised Rhythm and Voice Conversion to Improve ASR on Dysarthric SpeechCode0
LinearVC: Linear transformations of self-supervised features through the lens of voice conversion—0
SALF-MOS: Speaker Agnostic Latent Features Downsampled for MOS Prediction—0
Rhythm Controllable and Efficient Zero-Shot Voice Conversion via Shortcut Flow Matching—0
PseudoVC: Improving One-shot Voice Conversion with Pseudo Paired Data—0
A Perception-Based L2 Speech Intelligibility Indicator: Leveraging a Rater's Shadowing and Sequence-to-sequence Voice Conversion—0
Voice Conversion Improves Cross-Domain Robustness for Spoken Arabic Dialect Identification—0
When Humans Growl and Birds Speak: High-Fidelity Voice Conversion from Human to Animal and Designed Sounds—0
Discl-VC: Disentangled Discrete Tokens and In-Context Learning for Controllable Zero-Shot Voice Conversion—0
PromptEVC: Controllable Emotional Voice Conversion with Natural Language Prompts—0
REWIND: Speech Time Reversal for Enhancing Speaker Representations in Diffusion-based Voice Conversion—0
VibE-SVC: Vibrato Extraction with High-frequency F0 Contour for Singing Voice Conversion—0
ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis—0
Eta-WavLM: Efficient Speaker Identity Removal in Self-Supervised Speech Representations Using a Simple Linear Equation—0
Private kNN-VC: Interpretable Anonymization of Converted SpeechCode0
EZ-VC: Easy Zero-shot Any-to-Any Voice Conversion—0
ClapFM-EVC: High-Fidelity and Flexible Emotional Voice Conversion with Dual Control from Natural Language and Speech—0
Towards Inclusive ASR: Investigating Voice Conversion for Dysarthric Speech Recognition in Low-Resource LanguagesCode0
Investigating self-supervised features for expressive, multilingual voice conversion—0
Discrete Optimal Transport and Voice Conversion—0
Generative Adversarial Network based Voice Conversion: Techniques, Challenges, and Recent Advancements—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