https://github.com/Aavache/CAESynth
공식 코드CAESynth: Real-Time Timbre Interpolation and Pitch Control with Conditional Autoencoders
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
This is a general task that covers transforming audio inputs into audio outputs, not limited to existing PaperWithCode categories of Source Separation, Denoising, Classification, Recognition, etc.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
CAESynth: Real-Time Timbre Interpolation and Pitch Control with Conditional Autoencoders
Semi-Blind Source Separation for Nonlinear Acoustic Echo Cancellation
Differentiable All-pole Filters for Time-varying Audio Systems
Differentiable All-pole Filters for Time-varying Audio Systems
Differentiable All-pole Filters for Time-varying Audio Systems
Differentiable All-pole Filters for Time-varying Audio Systems
Differentiable All-pole Filters for Time-varying Audio Systems
ControlVC: Zero-Shot Voice Conversion with Time-Varying Controls on Pitch and Speed
Joint deconvolution and unsupervised source separation for data on the sphere
Music2Latent: Consistency Autoencoders for Latent Audio Compression
Sound2Synth: Interpreting Sound via FM Synthesizer Parameters Estimation
Drum-Aware Ensemble Architecture for Improved Joint Musical Beat and Downbeat Tracking
MF-PAM: Accurate Pitch Estimation through Periodicity Analysis and Multi-level Feature Fusion
Nonlinear Independent Component Analysis for Discrete-Time and Continuous-Time Signals
Melon Playlist Dataset: a public dataset for audio-based playlist generation and music tagging
Fetal ECG Extraction from Maternal ECG using Attention-based CycleGAN
Time Series Source Separation using Dynamic Mode Decomposition
Unsupervised Harmonic Parameter Estimation Using Differentiable DSP and Spectral Optimal Transport
Trace your sources in large-scale data: one ring to find them all
GPU-accelerated Guided Source Separation for Meeting Transcription
GPU-accelerated Guided Source Separation for Meeting Transcription
Differentiable All-pole Filters for Time-varying Audio Systems
SignalTrain: Profiling Audio Compressors with Deep Neural Networks
Scalable Convolutional Dictionary Learning with Constrained Recurrent Sparse Auto-encoders
HAAQI-Net: A Non-intrusive Neural Music Audio Quality Assessment Model for Hearing Aids
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.