Speaker Verification
171 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
Training-Free Deepfake Voice Recognition by Leveraging Large-Scale Pre-Trained Models
In this paper we study the potential of large-scale pre-trained models for audio deepfake detection, with special focus on generalization ability.
Converting Anyone's Voice: End-to-End Expressive Voice Conversion with a Conditional Diffusion Model
A major challenge of expressive VC lies in emotion prosody modeling.
A Comparison of Differential Performance Metrics for the Evaluation of Automatic Speaker Verification Fairness
When decisions are made and when personal data is treated by automated processes, there is an expectation of fairness -- that members of different demographic groups receive equitable treatment.
Efficient Multi-Model Fusion with Adversarial Complementary Representation Learning
Single-model systems often suffer from deficiencies in tasks such as speaker verification (SV) and image classification, relying heavily on partial prior knowledge during decision-making, resulting in suboptimal performance.
Additive Margin in Contrastive Self-Supervised Frameworks to Learn Discriminative Speaker Representations
Implementing these two modifications to SimCLR improves performance and results in 7. 85% EER on VoxCeleb1-O, outperforming other equivalent methods.
Text-dependent Speaker Verification (TdSV) Challenge 2024: Challenge Evaluation Plan
This document outlines the Text-dependent Speaker Verification (TdSV) Challenge 2024, which centers on analyzing and exploring novel approaches for text-dependent speaker verification.
Zero-Shot Multi-Lingual Speaker Verification in Clinical Trials
This represents a significant step in developing more versatile and efficient speaker verification systems for cognitive and mental health clinical trials that can be used across a wide range of languages and dialects, substantially reducing the effort required to develop speaker verification systems for multiple languages.
Asymmetric and trial-dependent modeling: the contribution of LIA to SdSV Challenge Task 2
The SdSv challenge Task 2 provided an opportunity to assess efficiency and robustness of modern text-independent speaker verification systems.
KunquDB: An Attempt for Speaker Verification in the Chinese Opera Scenario
This work aims to promote Chinese opera research in both musical and speech domains, with a primary focus on overcoming the data limitations.
Efficient Adapter Tuning of Pre-trained Speech Models for Automatic Speaker Verification
With excellent generalization ability, self-supervised speech models have shown impressive performance on various downstream speech tasks in the pre-training and fine-tuning paradigm.
