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 351–400 of 520 papers

TitleStatusHype
StarGAN-ZSVC: Towards Zero-Shot Voice Conversion in Low-Resource Contexts—0
Emotional Voice Conversion: Theory, Databases and ESDCode1
DiffSVC: A Diffusion Probabilistic Model for Singing Voice Conversion—0
Low-Latency Real-Time Non-Parallel Voice Conversion based on Cyclic Variational Autoencoder and Multiband WaveRNN with Data-Driven Linear PredictionCode1
Voice Conversion Based Speaker Normalization for Acoustic Unit Discovery—0
An Adaptive Learning based Generative Adversarial Network for One-To-One Voice Conversion—0
Deep Learning Based Assessment of Synthetic Speech NaturalnessCode1
Building Bilingual and Code-Switched Voice Conversion with Limited Training Data Using Embedding Consistency LossCode1
Towards end-to-end F0 voice conversion based on Dual-GAN with convolutional wavelet kernels—0
Non-autoregressive sequence-to-sequence voice conversion—0
NoiseVC: Towards High Quality Zero-Shot Voice Conversion—0
S2VC: A Framework for Any-to-Any Voice Conversion with Self-Supervised Pretrained RepresentationsCode1
Utilizing Self-supervised Representations for MOS PredictionCode0
StarGAN-based Emotional Voice Conversion for Japanese Phrases—0
Assem-VC: Realistic Voice Conversion by Assembling Modern Speech Synthesis TechniquesCode1
Speech Resynthesis from Discrete Disentangled Self-Supervised RepresentationsCode1
Limited Data Emotional Voice Conversion Leveraging Text-to-Speech: Two-stage Sequence-to-Sequence TrainingCode1
Improving Zero-shot Voice Style Transfer via Disentangled Representation Learning—0
Investigating on Incorporating Pretrained and Learnable Speaker Representations for Multi-Speaker Multi-Style Text-to-Speech—0
crank: An Open-Source Software for Nonparallel Voice Conversion Based on Vector-Quantized Variational AutoencoderCode1
MaskCycleGAN-VC: Learning Non-parallel Voice Conversion with Filling in FramesCode1
Axial Residual Networks for CycleGAN-based Voice Conversion—0
ASVspoof 2019: spoofing countermeasures for the detection of synthesized, converted and replayed speech—0
Towards Natural and Controllable Cross-Lingual Voice Conversion Based on Neural TTS Model and Phonetic Posteriorgram—0
High Fidelity Speech Regeneration with Application to Speech Enhancement—0
Adversarially learning disentangled speech representations for robust multi-factor voice conversion—0
Hierarchical disentangled representation learning for singing voice conversion—0
EmoCat: Language-agnostic Emotional Voice Conversion—0
Joint Audio-Visual Deepfake Detection—0
Adversarial Disentanglement of Speaker Representation for Attribute-Driven Privacy PreservationCode0
Phonetic Posteriorgrams based Many-to-Many Singing Voice Conversion via Adversarial TrainingCode1
How Far Are We from Robust Voice Conversion: A Survey—0
Low-resource expressive text-to-speech using data augmentation—0
FastSVC: Fast Cross-Domain Singing Voice Conversion with Feature-wise Linear ModulationCode1
Learning Explicit Prosody Models and Deep Speaker Embeddings for Atypical Voice Conversion—0
VAW-GAN for Disentanglement and Recomposition of Emotional Elements in Speech—0
Learning to Maximize Speech Quality Directly Using MOS Prediction for Neural Text-to-Speech—0
Seen and Unseen emotional style transfer for voice conversion with a new emotional speech datasetCode1
PPG-based singing voice conversion with adversarial representation learning—0
One-class learning towards generalized voice spoofing detectionCode1
FragmentVC: Any-to-Any Voice Conversion by End-to-End Extracting and Fusing Fine-Grained Voice Fragments With AttentionCode1
Voice Conversion Using Speech-to-Speech Neuro-Style TransferCode1
Any-to-One Sequence-to-Sequence Voice Conversion using Self-Supervised Discrete Speech Representations—0
CycleGAN-VC3: Examining and Improving CycleGAN-VCs for Mel-spectrogram ConversionCode1
Towards Natural Bilingual and Code-Switched Speech Synthesis Based on Mix of Monolingual Recordings and Cross-Lingual Voice Conversion—0
Baseline System of Voice Conversion Challenge 2020 with Cyclic Variational Autoencoder and Parallel WaveGANCode1
The NU Voice Conversion System for the Voice Conversion Challenge 2020: On the Effectiveness of Sequence-to-sequence Models and Autoregressive Neural Vocoders—0
FastVC: Fast Voice Conversion with non-parallel data—0
Latent linguistic embedding for cross-lingual text-to-speech and voice conversion—0
The Academia Sinica Systems of Voice Conversion for VCC2020—0
Show:102550
← PrevPage 8 of 11Next →
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