https://github.com/pwc-1/Paper-9/tree/main/hubert
HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units
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Speech Representation Learning
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/pyf98/dphubert
Structured Pruning of Self-Supervised Pre-trained Models for Speech Recognition and Understanding
https://github.com/richardbaihe/a3t
A$^3$T: Alignment-Aware Acoustic and Text Pretraining for Speech Synthesis and Editing
https://github.com/rongjiehuang/transpeech
TranSpeech: Speech-to-Speech Translation With Bilateral Perturbation
https://github.com/s3prl/s3prl
Mockingjay: Unsupervised Speech Representation Learning with Deep Bidirectional Transformer Encoders
https://github.com/samirsahoo007/Audio-and-Speech-Processing
An Unsupervised Autoregressive Model for Speech Representation Learning
https://github.com/sanyuan-chen/unispeech
UniSpeech-SAT: Universal Speech Representation Learning with Speaker Aware Pre-Training
https://github.com/swasun/VQ-VAE-Speech
Unsupervised speech representation learning using WaveNet autoencoders
https://github.com/wenet-e2e/wenet
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.