Speaker Verification
170 papers with code • 5 benchmarks • 6 datasets
Speaker verification is the verifying the identity of a person from characteristics of the voice.
( Image credit: Contrastive-Predictive-Coding-PyTorch )
Libraries
Use these libraries to find Speaker Verification models and implementations
VoxCeleb1
VoxCeleb2
VGG-Sound
CN-CELEB
EVI
Latest papers with no code
Enhancement of a Text-Independent Speaker Verification System by using Feature Combination and Parallel-Structure Classifiers
In this work, we propose the combination of two SVM-based classifiers with different kernel functions: Linear kernel and Gaussian Radial Basis Function (RBF) kernel with a Logistic Regression (LR) classifier.
Adversarial speech for voice privacy protection from Personalized Speech generation
For validation, we employ the open-source pre-trained YourTTS model for speech generation and protect the target speaker's speech in the white-box scenario.
Empowering Communication: Speech Technology for Indian and Western Accents through AI-powered Speech Synthesis
The architecture of the system comprises a speaker verification system, a synthesizer, a vocoder, and noise reduction.
Generalizing Speaker Verification for Spoof Awareness in the Embedding Space
To this end, we propose to generalize the standalone ASV (G-SASV) against spoofing attacks, where we leverage limited training data from CM to enhance a simple backend in the embedding space, without the involvement of a separate CM module during the test (authentication) phase.
ECAPA2: A Hybrid Neural Network Architecture and Training Strategy for Robust Speaker Embeddings
In this paper, we present ECAPA2, a novel hybrid neural network architecture and training strategy to produce robust speaker embeddings.
Exploratory Evaluation of Speech Content Masking
Most recent speech privacy efforts have focused on anonymizing acoustic speaker attributes but there has not been as much research into protecting information from speech content.
VOT: Revolutionizing Speaker Verification with Memory and Attention Mechanisms
Speaker verification is to judge the similarity of two unknown voices in an open set, where the ideal speaker embedding should be able to condense discriminant information into a compact utterance-level representation that has small intra-speaker distances and large inter-speaker distances. We propose a novel model named Voice Transformer(VOT) for speaker verification.
Scalable Ensemble-based Detection Method against Adversarial Attacks for speaker verification
Automatic speaker verification (ASV) is highly susceptible to adversarial attacks.
Lightweight Speaker Verification Using Transformation Module with Feature Partition and Fusion
The features that are output from current block of the model are processed according to the steps above before they are fed into the next block of the model.
LC4SV: A Denoising Framework Learning to Compensate for Unseen Speaker Verification Models
The performance of speaker verification (SV) models may drop dramatically in noisy environments.
