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 51–75 of 435 papers

TitleStatusHype
Speaker Characterization by means of Attention Pooling—0
Who is Authentic Speaker—0
Certification of Speaker Recognition Models to Additive PerturbationsCode0
Artificial Neural Networks to Recognize Speakers Division from Continuous Bengali Speech—0
TIMIT Speaker Profiling: A Comparison of Multi-task learning and Single-task learning Approaches—0
Voice Conversion Augmentation for Speaker Recognition on Defective Datasets—0
3D-Speaker-Toolkit: An Open-Source Toolkit for Multimodal Speaker Verification and DiarizationCode0
Asymmetric and trial-dependent modeling: the contribution of LIA to SdSV Challenge Task 2—0
Cosine Scoring with Uncertainty for Neural Speaker Embedding—0
ESPnet-SPK: full pipeline speaker embedding toolkit with reproducible recipes, self-supervised front-ends, and off-the-shelf modelsCode3
Post-Training Embedding Alignment for Decoupling Enrollment and Runtime Speaker Recognition Models—0
Voxceleb-ESP: preliminary experiments detecting Spanish celebrities from their voices—0
Vulnerability of Automatic Identity Recognition to Audio-Visual Deepfakes—0
Phonetic-aware speaker embedding for far-field speaker verification—0
Parrot-Trained Adversarial Examples: Pushing the Practicality of Black-Box Audio Attacks against Speaker Recognition Models—0
Personalizing Keyword Spotting with Speaker Information—0
Detecting Agreement in Multi-party Conversational AI—0
Deep Neural Networks for Automatic Speaker Recognition Do Not Learn Supra-Segmental Temporal Features—0
UniX-Encoder: A Universal X-Channel Speech Encoder for Ad-Hoc Microphone Array Speech Processing—0
Take the aTrain. Introducing an Interface for the Accessible Transcription of InterviewsCode3
Privacy-oriented manipulation of speaker representations—0
Thech. Report: Genuinization of Speech waveform PMF for speaker detection spoofing and countermeasures—0
Disentangling Voice and Content with Self-Supervision for Speaker Recognition—0
Leveraging In-the-Wild Data for Effective Self-Supervised Pretraining in Speaker RecognitionCode3
SLMIA-SR: Speaker-Level Membership Inference Attacks against Speaker Recognition SystemsCode0
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Benchmark Results

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