Papers with Code 아카이브
Audio Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 4
- 평가표
- 3
- 보존된 평가 기록
- 26
Audio generation (synthesis) is the task of generating raw audio such as speech.
<span style="color:grey; opacity: 0.6">( Image credit: MelNet )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/han-shi/SparseBERT
https://github.com/haoheliu/audioldm-training-finetuning
AudioLDM: Text-to-Audio Generation with Latent Diffusion Models
https://github.com/haoheliu/audioldm_eval
AudioLDM: Text-to-Audio Generation with Latent Diffusion Models
https://github.com/haoheliu/versatile_audio_super_resolution
https://github.com/hawkiyc/WaveGAN_for_12_Leads_ECG_Signals
https://github.com/huggingface/diffusers
AudioLDM: Text-to-Audio Generation with Latent Diffusion Models
https://github.com/ibab/tensorflow-wavenet
https://github.com/imdatsolak/wavenet
https://github.com/inconnu11/Objective-evaluation_speech_synthesis
https://github.com/isadrtdinov/wavenet
https://github.com/ivcylc/openmusic
Latent Swap Joint Diffusion for 2D Long-Form Latent Generation
https://github.com/ivcylc/qa-mdt
Latent Swap Joint Diffusion for 2D Long-Form Latent Generation
https://github.com/jackaduma/CycleGAN-VC2
https://github.com/jacksonkaunismaa/neural-music
MelNet: A Generative Model for Audio in the Frequency Domain
https://github.com/jinbo-hu/pseldnets
https://github.com/johnathanchiu/audio-upsampling
https://github.com/jonahwinninghoff/Text-Summarization
https://github.com/juanalonso/DDSP-singing-experiments
https://github.com/karpathy/makemore
https://github.com/kingridda/voice-cloning-AI
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
https://github.com/kingstarcraft/speech-to-text-wavenet2
https://github.com/kuleshov/audio-super-res
https://github.com/kyungyunlee/fins
Filtered Noise Shaping for Time Domain Room Impulse Response Estimation From Reverberant Speech
https://github.com/leolya/Audio-Super-Resolution-Tensorflow2.0-TFiLM
Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise Modulations
https://github.com/liguigui/speech-to-text-wavenet
https://github.com/liuhuadai/AudioLCM
AudioLCM: Text-to-Audio Generation with Latent Consistency Models
https://github.com/lonce/sonyGanFork
https://github.com/lucidrains/audiolm-pytorch
https://github.com/lucidrains/soundstorm-pytorch
https://github.com/mahotani/ADVERSARIAL-AUDIO-SYNTHESIS
https://github.com/majidAdibian77/persian-SV2TTS
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
https://github.com/maum-ai/nuwave
NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling
https://github.com/maum-ai/nuwave2
NU-Wave 2: A General Neural Audio Upsampling Model for Various Sampling Rates
https://github.com/mindspore-ai/models/tree/master/research/audio/wavenet
https://github.com/mindspore-lab/mindone/tree/master/examples/moviegen
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.