34 citations · 111 across the 28 of their papers we have counts for
29 papers
Diverse Audio Embeddings -- Bringing Features Back Outperforms CLAP!
Prateek Verma
With the advent of modern AI architectures, a shift has happened towards end-to-end architectures. This pivot has led to neural architectures being trained without domain-specific…
Neural Architectures Learning Fourier Transforms, Signal Processing and Much More....
Prateek Verma
This report will explore and answer fundamental questions about taking Fourier Transforms and tying it with recent advances in AI and neural architecture. One interpretation of the…
Seasonality Based Reranking of E-commerce Autocomplete Using Natural Language Queries
Prateek Verma, Shan Zhong, Xiaoyu Liu +1
Query autocomplete (QAC) also known as typeahead, suggests list of complete queries as user types prefix in the search box. It is one of the key features of modern search engines s…
Conformer LLMs -- Convolution Augmented Large Language Models
Prateek Verma
This work builds together two popular blocks of neural architecture, namely convolutional layers and Transformers, for large language models (LLMs). Non-causal conformers are used…
Developing Speech Processing Pipelines for Police Accountability
Anjalie Field, Prateek Verma, Nay San +2
Police body-worn cameras have the potential to improve accountability and transparency in policing. Yet in practice, they result in millions of hours of footage that is never revie…
Content Adaptive Front End For Audio Classification
Prateek Verma, Chris Chafe
We propose a learnable content adaptive front end for audio signal processing. Before the modern advent of deep learning, we used fixed representation non-learnable front-ends like…
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…
Generating Coherent Drum Accompaniment With Fills And Improvisations
Rishabh Dahale, Vaibhav Talwadker, Preeti Rao +1
Creating a complex work of art like music necessitates profound creativity. With recent advancements in deep learning and powerful models such as transformers, there has been huge…
Enhancing Audio Perception of Music By AI Picked Room Acoustics
Prateek Verma, Jonathan Berger
Every sound that we hear is the result of successive convolutional operations (e.g. room acoustics, microphone characteristics, resonant properties of the instrument itself, not to…
A Language Model With Million Context Length For Raw Audio
Prateek Verma
Modeling long-term dependencies for audio signals is a particularly challenging problem, as even small-time scales yield on the order of a hundred thousand samples. With the recent…
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…
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…
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…
Towards Human Haptic Gesture Interpretation for Robotic Systems
Bibit Bianchini, Prateek Verma, Kenneth Salisbury
Physical human-robot interactions (pHRI) are less efficient and communicative than human-human interactions, and a key reason is a lack of informative sense of touch in robotic sys…
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…
Self-Supervised Learning of Context-Aware Pitch Prosody Representations
Camille Noufi, Prateek Verma
In music and speech, meaning is derived at multiple levels of context. Affect, for example, can be inferred both by a short sound token and by sonic patterns over a longer temporal…
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…
Learning to Model Aspects of Hearing Perception Using Neural Loss Functions
Prateek Verma, Jonathan Berger
We present a framework to model the perceived quality of audio signals by combining convolutional architectures, with ideas from classical signal processing, and describe an approa…
Ranking sentences from product description & bullets for better search
Prateek Verma, Aliasgar Kutiyanawala, Ke Shen
Products in an ecommerce catalog contain information-rich fields like description and bullets that can be useful to extract entities (attributes) using NER based systems. However,…
Understanding and Classifying Cultural Music Using Melodic Features Case Of Hindustani, Carnatic And Turkish Music
Amruta Vidwans, Prateek Verma, Preeti Rao
We present a melody based classification of musical styles by exploiting the pitch and energy based characteristics derived from the audio signal. Three prominent musical styles we…
End-to-End Spoken Language Translation
Michelle Guo, Albert Haque, Prateek Verma
In this paper, we address the task of spoken language understanding. We present a method for translating spoken sentences from one language into spoken sentences in another languag…
Neuralogram: A Deep Neural Network Based Representation for Audio Signals
Prateek Verma, Chris Chafe, Jonathan Berger
We propose the Neuralogram -- a deep neural network based representation for understanding audio signals which, as the name suggests, transforms an audio signal to a dense, compact…