9 citations · 25 across the 11 of their papers we have counts for
14 papers
One-Shot Acoustic Matching Of Audio Signals -- Learning to Hear Music In Any Room/ Concert Hall
Prateek Verma, Chris Chafe, Jonathan Berger
The acoustic space in which a sound is created and heard plays an essential role in how that sound is perceived by affording a unique sense of \textit{presence}. Every sound we hea…
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…
A Framework for Generative and Contrastive Learning of Audio Representations
Prateek Verma, Julius Smith
In this paper, we present a framework for contrastive learning for audio representations, in a self supervised frame work without access to any ground truth labels. The core idea i…
Translating Paintings Into Music Using Neural Networks
Prateek Verma, Constantin Basica, Pamela Davis Kivelson
We propose a system that learns from artistic pairings of music and corresponding album cover art. The goal is to 'translate' paintings into music and, in further stages of develop…
A Deep Learning Approach for Low-Latency Packet Loss Concealment of Audio Signals in Networked Music Performance Applications
Prateek Verma, Alessandro Ilic Mezza, Chris Chafe +1
Networked Music Performance (NMP) is envisioned as a potential game changer among Internet applications: it aims at revolutionizing the traditional concept of musical interaction b…
Unsupervised Learning of Audio Perception for Robotics Applications: Learning to Project Data to T-SNE/UMAP space
Prateek Verma, Kenneth Salisbury
Audio perception is a key to solving a variety of problems ranging from acoustic scene analysis, music meta-data extraction, recommendation, synthesis and analysis. It can potentia…