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

Showing 311320 of 520 papers

TitleStatusHype
Disentanglement of Emotional Style and Speaker Identity for Expressive Voice Conversion0
Speech Enhancement-assisted Voice Conversion in Noisy Environments0
CycleFlow: Purify Information Factors by Cycle Loss0
FMFCC-A: A Challenging Mandarin Dataset for Synthetic Speech DetectionCode1
LDNet: Unified Listener Dependent Modeling in MOS Prediction for Synthetic SpeechCode1
Towards Identity Preserving Normal to Dysarthric Voice Conversion0
SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language ProcessingCode1
Toward Degradation-Robust Voice ConversionCode1
Exploring the Importance of F0 Trajectories for Speaker Anonymization using X-vectors and Neural Waveform Models0
DeepA: A Deep Neural Analyzer For Speech And Singing Vocoding0
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Benchmark Results

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