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 176–200 of 435 papers

TitleStatusHype
The Kriston AI System for the VoxCeleb Speaker Recognition Challenge 2022—0
The SpeakIn System Description for CNSRC2022—0
The ReturnZero System for VoxCeleb Speaker Recognition Challenge 2022—0
GIST-AiTeR System for the Diarization Task of the 2022 VoxCeleb Speaker Recognition Challenge—0
The Royalflush System for VoxCeleb Speaker Recognition Challenge 2022—0
A Benchmark for Understanding and Generating Dialogue between Characters in Stories—0
Disentangled Speaker Representation Learning via Mutual Information Minimization—0
Attention and DCT based Global Context Modeling for Text-independent Speaker Recognition—0
Perception-Aware Attack: Creating Adversarial Music via Reverse-Engineering Human Perception—0
Graph-based Multi-View Fusion and Local Adaptation: Mitigating Within-Household Confusability for Speaker Identification—0
A Hierarchical Speaker Representation Framework for One-shot Singing Voice Conversion—0
Towards End-to-End Private Automatic Speaker Recognition—0
AS2T: Arbitrary Source-To-Target Adversarial Attack on Speaker Recognition Systems—0
WeCanTalk: A New Multi-language, Multi-modal Resource for Speaker Recognition—0
Far-Field Speaker Recognition Benchmark Derived From The DiPCo Corpus—0
Dynamic Recognition of Speakers for Consent Management by Contrastive Embedding Replay—0
Baselines and Protocols for Household Speaker RecognitionCode0
Why does Self-Supervised Learning for Speech Recognition Benefit Speaker Recognition?—0
Graph Convolutional Network Based Semi-Supervised Learning on Multi-Speaker Meeting Data—0
The 2021 NIST Speaker Recognition Evaluation—0
The NIST CTS Speaker Recognition Challenge—0
Disentangled Speech Representation Learning Based on Factorized Hierarchical Variational Autoencoder with Self-Supervised Objective—0
Robust Speaker Recognition with Transformers Using wav2vec 2.0—0
Curriculum learning for self-supervised speaker verification—0
To train or not to train adversarially: A study of bias mitigation strategies for speaker recognitionCode0
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Benchmark Results

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