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 151–200 of 435 papers

TitleStatusHype
Speaker and Language Change Detection using Wav2vec2 and Whisper—0
Masking Kernel for Learning Energy-Efficient Representations for Speaker Recognition and Mobile HealthCode0
Audio Representation Learning by Distilling Video as Privileged Information—0
Leveraging Speaker Embeddings with Adversarial Multi-task Learning for Age Group Classification—0
A Multi-Purpose Audio-Visual Corpus for Multi-Modal Persian Speech Recognition: the Arman-AV Dataset—0
The Newsbridge -Telecom SudParis VoxCeleb Speaker Recognition Challenge 2022 System Description—0
Introducing Model Inversion Attacks on Automatic Speaker Recognition—0
SLUE Phase-2: A Benchmark Suite of Diverse Spoken Language Understanding Tasks—0
Probing Deep Speaker Embeddings for Speaker-related Tasks—0
A Novel Speech Feature Fusion Algorithm for Text-Independent Speaker Recognition—0
Inconsistency Ranking-based Noisy Label Detection for High-quality DataCode0
A new Speech Feature Fusion method with cross gate parallel CNN for Speaker Recognition—0
Multi-source Domain Adaptation for Text-independent Forensic Speaker Recognition—0
Is Style All You Need? Dependencies Between Emotion and GST-based Speaker RecognitionCode0
Late Audio-Visual Fusion for In-The-Wild Speaker Diarization—0
I4U System Description for NIST SRE'20 CTS Challenge—0
Disentangled representation learning for multilingual speaker recognition—0
Universal speaker recognition encoders for different speech segments duration—0
Self-Supervised Training of Speaker Encoder with Multi-Modal Diverse Positive Pairs—0
Improving Speech Representation Learning via Speech-level and Phoneme-level Masking Approach—0
Large-scale learning of generalised representations for speaker recognition—0
Risk of re-identification for shared clinical speech recordingsCode0
SUPERB @ SLT 2022: Challenge on Generalization and Efficiency of Self-Supervised Speech Representation Learning—0
THUEE system description for NIST 2020 SRE CTS challenge—0
The DKU-DukeECE Diarization System for the VoxCeleb Speaker Recognition Challenge 2022—0
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