I am currently a fourth year Ph.D. student in the Machine Learning Group at Princetons's Computer Science department. Currently, I am working with Dr. Adam Finkelstein.
My long-term research goal is to build conversational artificial intelligence agents spanning modalities like speech and language. Most of my current researchhas focusedon audio perception and machine learning, to that end designing perceptual objective metrics for evaluating audio quality.
In the past, I have interned at Facebook Reality Labs Research (FRLR) in Redmond, WA, and another one at Adobe Research in San Francisco, CA.
I completed my B.Tech from Indian Institute Of Technology, Guwahati in 2018 in Electronics and Electrical Engineering and Computer Science.
In the summer of 2017, I interned at Carnegie Mellon University, PA - advised by Dr. Bhiksha Raj, who leads the Machine Learning and Speech Processing Group at LTI-CMU. We worked on the problem of retrieving all semantically similar audio given a query clip. Devised a novel siamese neural network based approach which encodes the audio into a vector representation which is useful for retrieving similar recordings.
Previously, in the summer of 2016, I interned at Indian Institute of Technology, Delhi (IIT Delhi) advised by Dr. Tapan K. Gandhi, where I worked on various Machine Learning algorithms for analyzing and detecting the tumors in human brain using MR images. Designed a comprehensive tool where we could easily segment the tumor in the brain MR Image and then also see what 'Brodmann Area' it corresponds to.
- NORESQA : A Framework for Speech Quality Assessment using Non-Matching References
Pranay Manocha, Buye Xu, Anurag Kumar
To Appear - NeurIPS 2021
- DPLM: A Deep Perceptual Spatial-Audio Localization Metric
Pranay Manocha, Anurag Kumar, Buye Xu, Anjali Menon, Israel D. Gebru, Vamsi K. Ithapu, Paul Calamia
To Appear - WASPAA 2021
- CDPAM: Contrastive learning for perceptual audio similarity
Pranay Manocha, Zeyu Jin, Richard Zhang, Adam Finkelstein
ICASSP 2021 - Canada
- A Differentiable perceptual audio metric learned from just noticeable differences (best paper finalist!)
Pranay Manocha, Adam Finkelstein, Richard Zhang, Nicholas J. Bryan, Gautham J. Mysore, Zeyu Jin
Interspeech 2020, Shanghai - China
Paper Github Highlight Video Full Video
- Content-based Representations of audio using Siamese neural networks
Pranay Manocha, Rohan Badlani, Anurag Kumar, Ankit Shah, Benjamin Elizalde, Bhiksha Raj
ICASSP 2018 Calgary-Canada
- Brain Classification and Segmentation of MR Brain Images
Tanvi Gupta, Pranay Manocha, Tapan Kumar Gandhi, R.K Gupta, B.K Panigrahi
- Tumor Segmentation and Gradation for MR Brain Images
Tanvi Gupta, Pranay Manocha, R.K Gupta, Tapan Kumar Gandhi
Computational Intelligence and Communication Technology (CICT-2018)
- Automated tumor segmentation and brain mapping for the tumor area
Pranay Manocha, Snehal Bhasme, Tanvi Gupta, Tapan Kumar Gandhi
International Conference on Human-Computer Interaction - IHCI 2017