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
Voice Conversion Based Speaker Normalization for Acoustic Unit Discovery—0
Voice Conversion by Cascading Automatic Speech Recognition and Text-to-Speech Synthesis with Prosody Transfer—0
Voice Conversion Can Improve ASR in Very Low-Resource Settings—0
Voice Conversion Challenge 2020: Intra-lingual semi-parallel and cross-lingual voice conversion—0
Voice Conversion for Stuttered Speech, Instruments, Unseen Languages and Textually Described Voices—0
Voice Conversion for Whispered Speech Synthesis—0
Voice Conversion Improves Cross-Domain Robustness for Spoken Arabic Dialect Identification—0
Many-to-Many Voice Conversion using Cycle-Consistent Variational Autoencoder with Multiple Decoders—0
Voice Conversion Using Sequence-to-Sequence Learning of Context Posterior Probabilities—0
Voice Conversion with Conditional SampleRNN—0
Voice Conversion with Diverse Intonation using Conditional Variational Auto-Encoder—0
Voice Filter: Few-shot text-to-speech speaker adaptation using voice conversion as a post-processing module—0
VoiceMixer: Adversarial Voice Style Mixup—0
VoicePrompter: Robust Zero-Shot Voice Conversion with Voice Prompt and Conditional Flow Matching—0
VoiceWukong: Benchmarking Deepfake Voice Detection—0
Vowels and Prosody Contribution in Neural Network Based Voice Conversion Algorithm with Noisy Training Data—0
VQ-CTAP: Cross-Modal Fine-Grained Sequence Representation Learning for Speech Processing—0
VSVC: Backdoor attack against Keyword Spotting based on Voiceprint Selection and Voice Conversion—0
Vulnerability of Automatic Identity Recognition to Audio-Visual Deepfakes—0
WaveCycleGAN: Synthetic-to-natural speech waveform conversion using cycle-consistent adversarial networks—0
WaveNet 聲碼器及其於語音轉換之應用 (WaveNet Vocoder and its Applications in Voice Conversion) [In Chinese]—0
WavThruVec: Latent speech representation as intermediate features for neural speech synthesis—0
We Need Variations in Speech Generation: Sub-center Modelling for Speaker Embeddings—0
When Automatic Voice Disguise Meets Automatic Speaker Verification—0
When Humans Growl and Birds Speak: High-Fidelity Voice Conversion from Human to Animal and Designed Sounds—0
Who is Authentic Speaker—0
Zero-shot Voice Conversion via Self-supervised Prosody Representation Learning—0
Many-to-Many Voice Conversion with Out-of-Dataset Speaker Support—0
StableVC: Style Controllable Zero-Shot Voice Conversion with Conditional Flow Matching—0
StarGAN-based Emotional Voice Conversion for Japanese Phrases—0
StarGAN-VC+ASR: StarGAN-based Non-Parallel Voice Conversion Regularized by Automatic Speech Recognition—0
StarGAN-ZSVC: Towards Zero-Shot Voice Conversion in Low-Resource Contexts—0
StarVC: A Unified Auto-Regressive Framework for Joint Text and Speech Generation in Voice Conversion—0
Stepback: Enhanced Disentanglement for Voice Conversion via Multi-Task Learning—0
Streaming Voice Conversion Via Intermediate Bottleneck Features And Non-streaming Teacher Guidance—0
StreamVC: Real-Time Low-Latency Voice Conversion—0
StreamVoice+: Evolving into End-to-end Streaming Zero-shot Voice Conversion—0
StreamVoice: Streamable Context-Aware Language Modeling for Real-time Zero-Shot Voice Conversion—0
Stylebook: Content-Dependent Speaking Style Modeling for Any-to-Any Voice Conversion using Only Speech Data—0
SVSNet+: Enhancing Speaker Voice Similarity Assessment Models with Representations from Speech Foundation Models—0
Taco-VC: A Single Speaker Tacotron based Voice Conversion with Limited Data—0
Takin-VC: Expressive Zero-Shot Voice Conversion via Adaptive Hybrid Content Encoding and Enhanced Timbre Modeling—0
Text-free non-parallel many-to-many voice conversion using normalising flows—0
Textless NLP -- Zero Resource Challenge with Low Resource Compute—0
TGAVC: Improving Autoencoder Voice Conversion with Text-Guided and Adversarial Training—0
The Academia Sinica Systems of Voice Conversion for VCC2020—0
ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech—0
The Database and Benchmark for the Source Speaker Tracing Challenge 2024—0
The Effectiveness of Time Stretching for Enhancing Dysarthric Speech for Improved Dysarthric Speech Recognition—0
The exploitation of Multiple Feature Extraction Techniques for Speaker Identification in Emotional States under Disguised Voices—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