SOTAVerified

Speaker Recognition

Speaker Recognition is the process of identifying or confirming the identity of a person given his speech segments.

Source: Margin Matters: Towards More Discriminative Deep Neural Network Embeddings for Speaker Recognition

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–125 of 435 papers

TitleStatusHype
Bayesian calibration for forensic evidence reporting—0
Deep Speaker Embeddings for Far-Field Speaker Recognition on Short Utterances—0
Augmentation adversarial training for self-supervised speaker recognition—0
Deep Speaker Vectors for Semi Text-independent Speaker Verification—0
Black-box Adversarial Attacks on Commercial Speech Platforms with Minimal Information—0
DeepVOX: Discovering Features from Raw Audio for Speaker Recognition in Non-ideal Audio Signals—0
Blind score normalization method for PLDA based speaker recognition—0
Detecting Agreement in Multi-party Conversational AI—0
Detection and Analysis of Content Creator Collaborations in YouTube Videos using Face- and Speaker-Recognition—0
Differences in Speaker Individualising Information between Case Particles and Fillers in Spoken Japanese—0
Discriminatively Re-trained i-vector Extractor for Speaker Recognition—0
Disentangled representation learning for multilingual speaker recognition—0
Disentangled Speaker Representation Learning via Mutual Information Minimization—0
Disentangled Speech Embeddings using Cross-modal Self-supervision—0
Disentangled Speech Representation Learning Based on Factorized Hierarchical Variational Autoencoder with Self-Supervised Objective—0
Disentangling Voice and Content with Self-Supervision for Speaker Recognition—0
Dropout Regularization for Self-Supervised Learning of Transformer Encoder Speech Representation—0
Call My Net 2: A New Resource for Speaker Recognition—0
Dynamic Recognition of Speakers for Consent Management by Contrastive Embedding Replay—0
An Ensemble SVM-based Approach for Voice Activity Detection—0
Embeddings for DNN speaker adaptive training—0
End-to-end Recurrent Denoising Autoencoder Embeddings for Speaker Identification—0
End-to-end training of time domain audio separation and recognition—0
Enhancing Open-Set Speaker Identification through Rapid Tuning with Speaker Reciprocal Points and Negative Sample—0
Exploring the Integration of Speech Separation and Recognition with Self-Supervised Learning Representation—0
Show:102550
← PrevPage 5 of 18Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1w2v2-aamEER1.88—Unverified
2WavLM+ECAPA-TDNNEER0.39—Unverified