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 201–250 of 520 papers

TitleStatusHype
An Adaptive Learning based Generative Adversarial Network for One-To-One Voice Conversion—0
ACE-VC: Adaptive and Controllable Voice Conversion using Explicitly Disentangled Self-supervised Speech Representations—0
Improving Voice Conversion for Dissimilar Speakers Using Perceptual Losses—0
CycleFlow: Purify Information Factors by Cycle Loss—0
ASVspoof 2019: spoofing countermeasures for the detection of synthesized, converted and replayed speech—0
Custom Data Augmentation for low resource ASR using Bark and Retrieval-Based Voice Conversion—0
Disentanglement of Emotional Style and Speaker Identity for Expressive Voice Conversion—0
CTEFM-VC: Zero-Shot Voice Conversion Based on Content-Aware Timbre Ensemble Modeling and Flow Matching—0
ALO-VC: Any-to-any Low-latency One-shot Voice Conversion—0
Identifying Source Speakers for Voice Conversion based Spoofing Attacks on Speaker Verification Systems—0
How Far Are We from Robust Voice Conversion: A Survey—0
HLTCOE JHU Submission to the Voice Privacy Challenge 2024—0
Cross-speaker style transfer for text-to-speech using data augmentation—0
High-quality nonparallel voice conversion based on cycle-consistent adversarial network—0
High Fidelity Speech Regeneration with Application to Speech Enhancement—0
Improved disentangled speech representations using contrastive learning in factorized hierarchical variational autoencoder—0
Improve few-shot voice cloning using multi-modal learning—0
Improving child speech recognition with augmented child-like speech—0
Cross-Speaker Emotion Transfer for Low-Resource Text-to-Speech Using Non-Parallel Voice Conversion with Pitch-Shift Data Augmentation—0
Crossmodal Voice Conversion—0
A Spoofing Benchmark for the 2018 Voice Conversion Challenge: Leveraging from Spoofing Countermeasures for Speech Artifact Assessment—0
Improving Voice Quality in Speech Anonymization With Just Perception-Informed Losses—0
AlignSTS: Speech-to-Singing Conversion via Cross-Modal Alignment—0
Hierarchical Sequence to Sequence Voice Conversion with Limited Data—0
Cross-modal Face- and Voice-style Transfer—0
Individuality-Preserving Voice Conversion for Articulation Disorders Using Locality-Constrained NMF—0
Invertible Voice Conversion—0
Investigating Inter- and Intra-speaker Voice Conversion using Audiobooks—0
Hierarchical disentangled representation learning for singing voice conversion—0
Investigating self-supervised features for expressive, multilingual voice conversion—0
Cross-lingual Text-To-Speech with Flow-based Voice Conversion for Improved Pronunciation—0
GPU-Friendly Local Regression for Voice Conversion—0
Cross-lingual Knowledge Distillation via Flow-based Voice Conversion for Robust Polyglot Text-To-Speech—0
IQDUBBING: Prosody modeling based on discrete self-supervised speech representation for expressive voice conversion—0
GlowVC: Mel-spectrogram space disentangling model for language-independent text-free voice conversion—0
Iteratively Improving Speech Recognition and Voice Conversion—0
GenVC: Self-Supervised Zero-Shot Voice Conversion—0
Joint training framework for text-to-speech and voice conversion using multi-source Tacotron and WaveNet—0
Creating Personalized Synthetic Voices from Post-Glossectomy Speech with Guided Diffusion Models—0
Latent linguistic embedding for cross-lingual text-to-speech and voice conversion—0
LCM-SVC: Latent Diffusion Model Based Singing Voice Conversion with Inference Acceleration via Latent Consistency Distillation—0
LDM-SVC: Latent Diffusion Model Based Zero-Shot Any-to-Any Singing Voice Conversion with Singer Guidance—0
ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis—0
A Hierarchical Speaker Representation Framework for One-shot Singing Voice Conversion—0
Learning Paralinguistic Features from Audiobooks through Style Voice Conversion—0
Learning Singing From Speech—0
Generative Adversarial Network based Voice Conversion: Techniques, Challenges, and Recent Advancements—0
Generating and Detecting Various Types of Fake Image and Audio Content: A Review of Modern Deep Learning Technologies and Tools—0
Creating New Voices using Normalizing Flows—0
Generalization of Spectrum Differential based Direct Waveform Modification for Voice Conversion—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