… learning of audio representations. We posit that contextual temporal information can be
exploited in the case of general audio … (i) We propose Audio2Vec, a self-supervised learning task …

… audio. In our spatial alignment SSL, we differ with them in learning binaural sounds
representation. [… task, given two video/audio frames, to learn video/audio representations. We …

… , a self-supervised pre-training approach for learning a general-purpose representation of
audio. Our approach … We learn general-purpose audio representations from unlabeled data by …

… pretraining the encoder on the English Common Voice dataset and using the learned
representations … the method to changes in the pretraining dataset, in the audio data type and in the …

… pre-training method using Transformer based encoder to learn a general and robust high-level
representation … by a large amount of unlabeled audio from various kinds of datasets. After …

… ) model for speech representation learning, with a unified pretraining object to leverage
different data sources, including paired visual-audio, audio-text, and unpaired audio and text1. …

… We propose learning generalpurpose audio representation from a single audio segment
with… Experimental Setup We repeated the cycle of pretraining and evaluation and averaged the …

… At the pre-training stage, we train our models with learning rate 5e-5, batch size 50, and
AdamW optimizer [26] for 500k steps. The models are pre-trained on a single NVIDIA Tesla …

… of constrastive learning of audio representations with the aid … video is not crucial to learn
strong audio representations. This … We pretrain our models on AudioSet [26] sampled at 16 kHz. …

… For pre-training, our BYOL variant framework with audio data augmentations learns a … We
adopt BYOL and learn representations invariant to input changes, relying on the changes of …