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
Certification of Speaker Recognition Models to Additive PerturbationsCode0
Pretext Tasks selection for multitask self-supervised speech representation learningCode0
Centroid-based deep metric learning for speaker recognition—0
CEC: A Noisy Label Detection Method for Speaker Recognition—0
A Reinforcement Learning Framework for Online Speaker Diarization—0
Can We Use Speaker Recognition Technology to Attack Itself? Enhancing Mimicry Attacks Using Automatic Target Speaker Selection—0
Dynamic Recognition of Speakers for Consent Management by Contrastive Embedding Replay—0
Arabic Speech Rhythm Corpus: Read and Spontaneous Speaking Styles—0
A Machine of Few Words -- Interactive Speaker Recognition with Reinforcement Learning—0
Call My Net 2: A New Resource for Speaker Recognition—0
Disentangled Speech Representation Learning Based on Factorized Hierarchical Variational Autoencoder with Self-Supervised Objective—0
BUT VOiCES 2019 System Description—0
基於數字文本相關之語者驗證系統的研究與實作 (Study and Implementation on Digit-related Speaker Verification) [In Chinese]—0
Disentangled Speech Embeddings using Cross-modal Self-supervision—0
Disentangled Speaker Representation Learning via Mutual Information Minimization—0
Disentangling Voice and Content with Self-Supervision for Speaker Recognition—0
Dropout Regularization for Self-Supervised Learning of Transformer Encoder Speech Representation—0
BUT System Description to VoxCeleb Speaker Recognition Challenge 2019—0
Disentangled representation learning for multilingual speaker recognition—0
Discriminatively Re-trained i-vector Extractor for Speaker Recognition—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
Building and Evaluation of a Real Room Impulse Response Dataset—0
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Benchmark Results

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