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 251–300 of 520 papers

TitleStatusHype
SpeechComposer: Unifying Multiple Speech Tasks with Prompt Composition—0
Speech Enhancement-assisted Voice Conversion in Noisy Environments—0
Speech Recognition for Automatically Assessing Afrikaans and isiXhosa Preschool Oral Narratives—0
ZSVC: Zero-shot Style Voice Conversion with Disentangled Latent Diffusion Models and Adversarial Training—0
Automatic Voice Identification after Speech Resynthesis using PPG—0
RT-VC: Real-Time Zero-Shot Voice Conversion with Speech Articulatory Coding—0
AASIST3: KAN-Enhanced AASIST Speech Deepfake Detection using SSL Features and Additional Regularization for the ASVspoof 2024 Challenge—0
ACE-VC: Adaptive and Controllable Voice Conversion using Explicitly Disentangled Self-supervised Speech Representations—0
A Comparative Analysis Of Latent Regressor Losses For Singing Voice Conversion—0
A Comparative Study of Voice Conversion Models with Large-Scale Speech and Singing Data: The T13 Systems for the Singing Voice Conversion Challenge 2023—0
AC-VC: Non-parallel Low Latency Phonetic Posteriorgrams Based Voice Conversion—0
Adaptive Speech Duration Modification using a Deep-Generative Framework—0
AdaptVC: High Quality Voice Conversion with Adaptive Learning—0
A Deep-Bayesian Framework for Adaptive Speech Duration Modification—0
Adversarially learning disentangled speech representations for robust multi-factor voice conversion—0
Adversarially Trained Autoencoders for Parallel-Data-Free Voice Conversion—0
Adversarial Speaker Disentanglement Using Unannotated External Data for Self-supervised Representation Based Voice Conversion—0
Adversarial speech for voice privacy protection from Personalized Speech generation—0
Adversarial Transformation of Spoofing Attacks for Voice Biometrics—0
AE-Flow: AutoEncoder Normalizing Flow—0
A Hierarchical Speaker Representation Framework for One-shot Singing Voice Conversion—0
AlignSTS: Speech-to-Singing Conversion via Cross-Modal Alignment—0
ALO-VC: Any-to-any Low-latency One-shot Voice Conversion—0
An Adaptive Learning based Generative Adversarial Network for One-To-One Voice Conversion—0
Analysis of Voice Conversion and Code-Switching Synthesis Using VQ-VAE—0
An Exhaustive Evaluation of TTS- and VC-based Data Augmentation for ASR—0
An Objective Evaluation Framework for Pathological Speech Synthesis—0
An Overview & Analysis of Sequence-to-Sequence Emotional Voice Conversion—0
An overview of text-to-speech systems and media applications—0
Anti-Spoofing Using Transfer Learning with Variational Information Bottleneck—0
Any-to-One Sequence-to-Sequence Voice Conversion using Self-Supervised Discrete Speech Representations—0
A Perception-Based L2 Speech Intelligibility Indicator: Leveraging a Rater's Shadowing and Sequence-to-sequence Voice Conversion—0
A Pilot Study of Applying Sequence-to-Sequence Voice Conversion to Evaluate the Intelligibility of L2 Speech Using a Native Speaker's Shadowings—0
Application of ASV for Voice Identification after VC and Duration Predictor Improvement in TTS Models—0
A Preliminary Study of a Two-Stage Paradigm for Preserving Speaker Identity in Dysarthric Voice Conversion—0
SongBsAb: A Dual Prevention Approach against Singing Voice Conversion based Illegal Song Covers—0
Are disentangled representations all you need to build speaker anonymization systems?—0
A Regression Model of Recurrent Deep Neural Networks for Noise Robust Estimation of the Fundamental Frequency Contour of Speech—0
ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis—0
A Spoofing Benchmark for the 2018 Voice Conversion Challenge: Leveraging from Spoofing Countermeasures for Speech Artifact Assessment—0
ASVspoof 2019: spoofing countermeasures for the detection of synthesized, converted and replayed speech—0
ASVspoof 5: Design, Collection and Validation of Resources for Spoofing, Deepfake, and Adversarial Attack Detection Using Crowdsourced Speech—0
Attention-based Interactive Disentangling Network for Instance-level Emotional Voice Conversion—0
Attentive activation function for improving end-to-end spoofing countermeasure systems—0
AttS2S-VC: Sequence-to-Sequence Voice Conversion with Attention and Context Preservation Mechanisms—0
Audio Anti-spoofing Using a Simple Attention Module and Joint Optimization Based on Additive Angular Margin Loss and Meta-learning—0
Audio Deep Fake Detection System with Neural Stitching for ADD 2022—0
A Unified Model For Voice and Accent Conversion In Speech and Singing using Self-Supervised Learning and Feature Extraction—0
AutoCycle-VC: Towards Bottleneck-Independent Zero-Shot Cross-Lingual Voice Conversion—0
Automatic Speech Disentanglement for Voice Conversion using Rank Module and Speech Augmentation—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