164 citations · 760 across the 31 of their papers we have counts for
4 papers · 1 filter
SSAST: Self-Supervised Audio Spectrogram Transformer
Yuan Gong, Cheng-I Jeff Lai, Yu-An Chung +1
Recently, neural networks based purely on self-attention, such as the Vision Transformer (ViT), have been shown to outperform deep learning models constructed with convolutional ne…
AST: Audio Spectrogram Transformer
Yuan Gong, Yu-An Chung, James Glass
In the past decade, convolutional neural networks (CNNs) have been widely adopted as the main building block for end-to-end audio classification models, which aim to learn a direct…
PSLA: Improving Audio Tagging with Pretraining, Sampling, Labeling, and Aggregation
Yuan Gong, Yu-An Chung, James Glass
Audio tagging is an active research area and has a wide range of applications. Since the release of AudioSet, great progress has been made in advancing model performance, which mos…
Audio Word2Vec: Unsupervised Learning of Audio Segment Representations using Sequence-to-sequence Autoencoder
Yu-An Chung, Chao-Chung Wu, Chia-Hao Shen +2
The vector representations of fixed dimensionality for words (in text) offered by Word2Vec have been shown to be very useful in many application scenarios, in particular due to the…