34 citations · 111 across the 28 of their papers we have counts for
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cs.SD2021
Attention is All You Need? Good Embeddings with Statistics are enough:Large Scale Audio Understanding without Transformers/ Convolutions/ BERTs/ Mixers/ Attention/ RNNs or ....
Prateek Verma
This paper presents a way of doing large scale audio understanding without traditional state of the art neural architectures. Ever since the introduction of deep learning for under…
cs.SD2021★ 2 cited
A Generative Model for Raw Audio Using Transformer Architectures
Prateek Verma, Chris Chafe
This paper proposes a novel way of doing audio synthesis at the waveform level using Transformer architectures. We propose a deep neural network for generating waveforms, similar t…
cs.SD2021★ 34 cited
Audio Transformers
Prateek Verma, Jonathan Berger
Over the past two decades, CNN architectures have produced compelling models of sound perception and cognition, learning hierarchical organizations of features. Analogous to succes…