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 401–450 of 520 papers

TitleStatusHype
Non-autoregressive sequence-to-sequence voice conversion—0
NoiseVC: Towards High Quality Zero-Shot Voice Conversion—0
Utilizing Self-supervised Representations for MOS PredictionCode0
StarGAN-based Emotional Voice Conversion for Japanese Phrases—0
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
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
How Far Are We from Robust Voice Conversion: A Survey—0
Low-resource expressive text-to-speech using data augmentation—0
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
PPG-based singing voice conversion with adversarial representation learning—0
Any-to-One Sequence-to-Sequence Voice Conversion using Self-Supervised Discrete Speech Representations—0
Towards Natural Bilingual and Code-Switched Speech Synthesis Based on Mix of Monolingual Recordings and Cross-Lingual Voice Conversion—0
The NU Voice Conversion System for the Voice Conversion Challenge 2020: On the Effectiveness of Sequence-to-sequence Models and Autoregressive Neural Vocoders—0
Latent linguistic embedding for cross-lingual text-to-speech and voice conversion—0
FastVC: Fast Voice Conversion with non-parallel data—0
The Sequence-to-Sequence Baseline for the Voice Conversion Challenge 2020: Cascading ASR and TTSCode0
The Academia Sinica Systems of Voice Conversion for VCC2020—0
When Automatic Voice Disguise Meets Automatic Speaker Verification—0
Voice Conversion by Cascading Automatic Speech Recognition and Text-to-Speech Synthesis with Prosody Transfer—0
Voice Conversion Challenge 2020: Intra-lingual semi-parallel and cross-lingual voice conversion—0
DeepSonar: Towards Effective and Robust Detection of AI-Synthesized Fake Voices—0
Spectrum and Prosody Conversion for Cross-lingual Voice Conversion with CycleGAN—0
VAW-GAN for Singing Voice Conversion with Non-parallel Training Data—0
Deep MOS Predictor for Synthetic Speech Using Cluster-Based Modeling—0
Unsupervised Cross-Domain Singing Voice Conversion—0
Neural MOS Prediction for Synthesized Speech Using Multi-Task Learning With Spoofing Detection and Spoofing Type Classification—0
Defense for Black-box Attacks on Anti-spoofing Models by Self-Supervised LearningCode0
NAUTILUS: a Versatile Voice Cloning System—0
Generative Adversarial Training Data Adaptation for Very Low-resource Automatic Speech RecognitionCode0
Many-to-Many Voice Transformer Network—0
Vowels and Prosody Contribution in Neural Network Based Voice Conversion Algorithm with Noisy Training Data—0
Comparison of Speech Representations for Automatic Quality Estimation in Multi-Speaker Text-to-Speech SynthesisCode0
Many-to-Many Voice Conversion using Conditional Cycle-Consistent Adversarial Networks—0
Vocoder-free End-to-End Voice Conversion with Transformer NetworkCode0
Mel-spectrogram augmentation for sequence to sequence voice conversionCode0
Learning Singing From Speech—0
Voice Conversion for Whispered Speech Synthesis—0
Towards Robust Neural Vocoding for Speech Generation: A Survey—0
PitchNet: Unsupervised Singing Voice Conversion with Pitch Adversarial Network—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