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Speaker Recognition
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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
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/google/speaker-id/tree/master/lingvo
공식 코드Dr-Vectors: Decision Residual Networks and an Improved Loss for Speaker Recognition
https://github.com/hechmik/voxceleb_enrichment_age_gender
공식 코드https://github.com/huashen218/voxceleb-fairness
공식 코드Improving fairness in speaker verification via Group-adapted Fusion Network
https://github.com/idiap/ssl-caller-detection
공식 코드Can Self-Supervised Neural Representations Pre-Trained on Human Speech distinguish Animal Callers?
https://github.com/iip-sogang/olkavs-avspeech
공식 코드OLKAVS: An Open Large-Scale Korean Audio-Visual Speech Dataset
https://github.com/iiscleap/E2E-NPLDA
공식 코드https://github.com/iiscleap/NeuralPlda
공식 코드https://github.com/jaesunghuh/voxsrc2022
공식 코드VoxSRC 2022: The Fourth VoxCeleb Speaker Recognition Challenge
https://github.com/joaoantoniocn/AM-MobileNet1D
공식 코드https://github.com/joaoantoniocn/AM-SincNet
공식 코드https://github.com/jongli747/curricular-sincnet
공식 코드https://github.com/josepatino/Voice-Privacy-Challenge-2020
공식 코드https://github.com/kaistmm/seed-pytorch
공식 코드https://github.com/kaistmm/voxsim_trainer
공식 코드https://github.com/machine-listeners-valencia/fsl_osr_dataset_baseline
공식 코드https://github.com/massabaali7/colmbo
공식 코드https://github.com/mechanicalsea/sugar
공식 코드EfficientTDNN: Efficient Architecture Search for Speaker Recognition
https://github.com/modelscope/3D-Speaker
공식 코드3D-Speaker-Toolkit: An Open-Source Toolkit for Multimodal Speaker Verification and Diarization
https://github.com/morganlee123/deeptalkemotions
공식 코드Is Style All You Need? Dependencies Between Emotion and GST-based Speaker Recognition
https://github.com/morganlee123/evector
공식 코드Vocal Style Factorization for Effective Speaker Recognition in Affective Scenarios
https://github.com/mpariente/AsSteroid
공식 코드https://github.com/mravanelli/SincNet
공식 코드https://github.com/msh9184/contrastive-equilibrium-learning
공식 코드Unsupervised Representation Learning for Speaker Recognition via Contrastive Equilibrium Learning
https://github.com/neurology-ai-program/speech_risk
공식 코드Risk of re-identification for shared clinical speech recordings
https://github.com/nikvaessen/w2v2-speaker
공식 코드https://github.com/nikvaessen/w2v2-speaker-few-samples
공식 코드https://github.com/rperi/trustworthy-asv-fairness
공식 코드https://github.com/s3l-official/slmia-sr
공식 코드SLMIA-SR: Speaker-Level Membership Inference Attacks against Speaker Recognition Systems
https://github.com/s3prl/s3prl
공식 코드TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech
https://github.com/salah-zaiem/PL-groupselection
공식 코드Pretext Tasks selection for multitask self-supervised speech representation learning
https://github.com/salah-zaiem/Pseudo-Label-Selection
공식 코드https://github.com/seongmin-kye/meta-SR
공식 코드Meta-Learning for Short Utterance Speaker Recognition with Imbalance Length Pairs
https://github.com/shareefbabu/covid_data_telephone_band
공식 코드COVID-19 Patient Detection from Telephone Quality Speech Data
https://github.com/shkim816/temporal_dynamic_cnn
공식 코드https://github.com/sholokhovalexey/online-speaker-clustering
공식 코드Probabilistic Back-ends for Online Speaker Recognition and Clustering
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.