survery of self supervised leraning for speech

Name	Paper	Comment	Organization	Source	Pre-trained model
vq-APC	Vector-Quantized Autoregressive Predictive Coding	Interspeech 2020	MIT	code
wav2vec 2.0	wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations	NeurIPS 2020	Facebook AI Research	code	models
CPC_audio	UNSUPERVISED PRETRAINING TRANSFERS WELL ACROSS LANGUAGES	ICASSP 2020	Facebook AI Research	code
APC	An unsuper- vised autoregressive model for speech representation learning	Interspeech 2019	MIT
vq-wav2vec	VQ-WAV2VEC: SELF-SUPERVISED LEARNING OF DISCRETE SPEECH REPRESENTATIONS	ICLR 2020	Facebook AI Research	code	models
wav2vec	wav2vec: Unsupervised Pre-Training for Speech Recognition	Interspeech 2019	Facebook AI Research	code	models

Applications

Name	Paper	Comment	Organization	Source	Pre-trained model
	Self-training and Pre-training are Complementary for Speech Recognition		Facebook AI Research

Name	Paper	Organization
	Towards Semi-Supervised Semantics Understanding from Speech	MIT/Amazon
	The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling
C/A/MPC	Similarity Analysis of Self-Supervised Speech Representations	MIT
DAPC	Representation Learning for Sequence Data with Deep Autoencoding Predictive Components	Cornell
BertVideo	VideoBERT: A Joint Model for Video and Language Representation Learning	Google