https://github.com/yzyouzhang/sasv_pr
공식 코드A Probabilistic Fusion Framework for Spoofing Aware Speaker Verification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Speaker verification is the verifying the identity of a person from characteristics of the voice.
<span style="color:grey; opacity: 0.6">( Image credit: Contrastive-Predictive-Coding-PyTorch )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
A Probabilistic Fusion Framework for Spoofing Aware Speaker Verification
On the Detection of Adaptive Adversarial Attacks in Speaker Verification Systems
Attack on practical speaker verification system using universal adversarial perturbations
rVAD: An Unsupervised Segment-Based Robust Voice Activity Detection Method
rVAD: An Unsupervised Segment-Based Robust Voice Activity Detection Method
rVAD: An Unsupervised Segment-Based Robust Voice Activity Detection Method
Attention-Based Models for Text-Dependent Speaker Verification
Defense for Black-box Attacks on Anti-spoofing Models by Self-Supervised Learning
Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data
Text-Independent Speaker Verification Using 3D Convolutional Neural Networks
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
AutoSpeech: Neural Architecture Search for Speaker Recognition
A Speaker Verification Backend for Improved Calibration Performance across Varying Conditions
Utterance-level Aggregation For Speaker Recognition In The Wild
AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.