Voice Conversion
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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
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/hcy71o/autovocoder
https://github.com/huawei-noah/Speech-Backbones/tree/main/Grad-TTS
Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme
https://github.com/huggingface/transformers
SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
https://github.com/hujinsen/pytorch-StarGAN-VC
StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networks
https://github.com/hzuppur/Cotatron
Cotatron: Transcription-Guided Speech Encoder for Any-to-Many Voice Conversion without Parallel Data
https://github.com/inconnu11/Objective-evaluation_speech_synthesis
Speech Resynthesis from Discrete Disentangled Self-Supervised Representations
https://github.com/issam9/finetuning-bert-models-for-arabic-dialect-detection
AraBERT: Transformer-based Model for Arabic Language Understanding
https://github.com/jackaduma/CycleGAN-VC2
Voice Conversion from Non-parallel Corpora Using Variational Auto-encoder
https://github.com/jackaduma/CycleGAN-VC3
CycleGAN-VC3: Examining and Improving CycleGAN-VCs for Mel-spectrogram Conversion
https://github.com/jaejunl/hyface
Hear Your Face: Face-based voice conversion with F0 estimation
https://github.com/jefflai108/ASSERT
ASSERT: Anti-Spoofing with Squeeze-Excitation and Residual neTworks
https://github.com/jlian2/Improved-Voice-Conversion-with-Conditional-DSVAE
Towards Improved Zero-shot Voice Conversion with Conditional DSVAE
https://github.com/jlian2/Robust-Voice-Style-Transfer
Robust Disentangled Variational Speech Representation Learning for Zero-shot Voice Conversion
https://github.com/joselyn-rodriguez/s3prl
Defense for Black-box Attacks on Anti-spoofing Models by Self-Supervised Learning
https://github.com/kaen2891/kaen2891.github.io
Vocoder-free End-to-End Voice Conversion with Transformer Network
https://github.com/keonlee9420/STYLER
Unsupervised Speech Decomposition via Triple Information Bottleneck
https://github.com/knurpsbram/autovc_wavenetvocoder_griffinlim_experiments
AUTOVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss
https://github.com/ktho22/vctts
Emotional Voice Conversion using Multitask Learning with Text-to-speech
https://github.com/kunzhou9646/mixed_emotions
https://github.com/liusongxiang/ppg-vc
Any-to-Many Voice Conversion with Location-Relative Sequence-to-Sequence Modeling
https://github.com/lucas-dunker/stem-separator-amt
https://github.com/makcedward/nlpaug
Mel-spectrogram augmentation for sequence to sequence voice conversion
https://github.com/maratsubkhankulov/cyclegan-vc
Parallel-Data-Free Voice Conversion Using Cycle-Consistent Adversarial Networks
https://github.com/marcoppasini/MelGAN-VC
MelGAN-VC: Voice Conversion and Audio Style Transfer on arbitrarily long samples using Spectrograms
https://github.com/maum-ai/voicefilter
Cotatron: Transcription-Guided Speech Encoder for Any-to-Many Voice Conversion without Parallel Data
https://github.com/mbzuai-nlp/artst
SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
https://github.com/mbzuai-nlp/sttatts
SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
https://github.com/mmakiuchi/multimodal_emotion_recognition
AUTOVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss
https://github.com/mramly/CairoMent
AraBERT: Transformer-based Model for Arabic Language Understanding
https://github.com/msfasha/Arabic-NLP
AraBERT: Transformer-based Model for Arabic Language Understanding
https://github.com/n1243645679976/svsnet
SVSNet: An End-to-end Speaker Voice Similarity Assessment Model
https://github.com/nafiuny/ICRCycleGAN-VC
Voice Conversion from Non-parallel Corpora Using Variational Auto-encoder
https://github.com/ntia/alignnet
MOSNet: Deep Learning based Objective Assessment for Voice Conversion
https://github.com/nvcnet/nvcnet.github.io
https://github.com/ozora-ogino/LCNN
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.