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Speaker Identification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mbar0075/speech-technology
공식 코드https://github.com/microsoft/speecht5
공식 코드SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
https://github.com/microsoft/unispeech
공식 코드UniSpeech-SAT: Universal Speech Representation Learning with Speaker Aware Pre-Training
https://github.com/midas-research/audino
공식 코드https://github.com/mmmmayi/pl-eesr
공식 코드PL-EESR: Perceptual Loss Based END-TO-END Robust Speaker Representation Extraction
https://github.com/mravanelli/SincNet
공식 코드https://github.com/nervjack2/melhubert
공식 코드https://github.com/nttcslab/eval-audio-repr
공식 코드Masked Modeling Duo: Towards a Universal Audio Pre-training Framework
https://github.com/nttcslab/m2d
공식 코드Masked Modeling Duo: Learning Representations by Encouraging Both Networks to Model the Input
https://github.com/rrbluke/BSSD
공식 코드Blind Speech Separation and Dereverberation using Neural Beamforming
https://github.com/sara-ahmed/asit
공식 코드ASiT: Local-Global Audio Spectrogram vIsion Transformer for Event Classification
https://github.com/seongmin-kye/meta-SR
공식 코드Meta-Learning for Short Utterance Speaker Recognition with Imbalance Length Pairs
https://github.com/siavashshams/ssamba
공식 코드SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Model
https://github.com/slash0bz/speaker-identification
공식 코드Cross-Lingual Speaker Identification Using Distant Supervision
https://github.com/sumafuture/SIG
공식 코드SIG: Speaker Identification in Literature via Prompt-Based Generation
https://github.com/tan-openlab/pf-net
공식 코드PF-Net: Personalized Filter for Speaker Recognition from Raw Waveform
https://github.com/tvuong123/ModulationDomainLoss
공식 코드A Modulation-Domain Loss for Neural-Network-based Real-time Speech Enhancement
https://github.com/wjk0925/slt2024-speechllm-speaker-understanding
공식 코드https://github.com/wngh1187/exu-net
공식 코드Extended U-Net for Speaker Verification in Noisy Environments
https://github.com/xl2248/csa-nct
공식 코드Towards Making the Most of Dialogue Characteristics for Neural Chat Translation
https://github.com/yellow-binary-tree/friends-mmc
공식 코드Friends-MMC: A Dataset for Multi-modal Multi-party Conversation Understanding
https://github.com/008karan/SincNet_demo
https://github.com/2023-MindSpore-4/Code8/tree/main/ats
ATST: Audio Representation Learning with Teacher-Student Transformer
https://github.com/2024-MindSpore-1/Code6/tree/main/ats
ATST: Audio Representation Learning with Teacher-Student Transformer
https://github.com/AI-Guru/SincNet
https://github.com/Alexander-H-Liu/NPC
Generative Pre-Training for Speech with Autoregressive Predictive Coding
https://github.com/AryaAftab/sincnet-tensorflow
https://github.com/Audio-WestlakeU/ATST-SED
ATST: Audio Representation Learning with Teacher-Student Transformer
https://github.com/Aurora11111/speaker-recognition-pytorch
https://github.com/Aurora11111/voiceprint
https://github.com/Edresson/VoiceSplit
Speech2Phone: A Novel and Efficient Method for Training Speaker Recognition Models
https://github.com/HHousen/speaker-change-detection
https://github.com/IanChan711/ATM_ide
https://github.com/JeongwookUm/TEST_AutoSpeech-master
AutoSpeech: Neural Architecture Search for Speaker Recognition
https://github.com/Js-Mim/rl_singing_voice
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.