Pranay Manocha
Email pmanocha at cs dot princeton dot eduAddress: 413, 35 Olden Street, Princeton, NJ, 08542
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About
Hi!
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 research has focused on audio perception and machine learning, to that end designing perceptual objective metrics for evaluating audio quality.
During my PhD, I have interned twice at Facebook Reality Labs Research (FRLR) in Redmond, WA, and at Adobe Research in San Francisco, CA. Before that, during undergrad, I have spent time at Carnegie Mellon University under the guidance of Dr. Bhiksha Raj working on retrieving semantically similar sounds. I have also spent time 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.
I completed my B.Tech from Indian Institute Of Technology, Guwahati in 2018 in Electronics and Electrical Engineering and Computer Science.
Publications
- Audio Similarity is Unreliable as a Proxy for Audio Quality
Pranay Manocha, Zeyu Jin, Adam Finkelstein
To Appear - Interspeech 2022
Paper - Speech Quality Assessment through MOS using Non-Matching References
Pranay Manocha, Anurag Kumar
To Appear - Interspeech 2022
Paper - SAQAM: Spatial Audio Quality Assessment Metric
Pranay Manocha, Anurag Kumar, Buye Xu, Anjali Menon, Israel D. Gebru, Vamsi K. Ithapu, Paul Calamia
To Appear - Interspeech 2022
Paper - SQAPP: No-Reference Speech Quality Assessment Via Pairwise Preference
Pranay Manocha, Zeyu Jin, Adam Finkelstein
ICASSP 2022
Paper Full Video - HEAR: Holistic Evaluation of Audio Representations
(#) Joseph Turian, Jordie Shier, Humair Raj Khan, Bhiksha Raj, Björn W. Schuller, Christian J. Steinmetz, Colin Malloy, George Tzanetakis, Gissel Velarde, Kirk McNally, Max Henry, Nicolas Pinto, Camille Noufi, Christian Clough, Dorien Herremans, Eduardo Fonseca, Jesse Engel, Justin Salamon, Philippe Esling, Pranay Manocha, Shinji Watanabe, Zeyu Jin, Yonatan Bisk
Proceedings of Machine Learning Research (PMLR): NeurIPS 2021 Competition Track
Paper Code Web Talks - NORESQA : A Framework for Speech Quality Assessment using Non-Matching References
Pranay Manocha, Buye Xu, Anurag Kumar
NeurIPS 2021
Paper Full Video Github - DPLM: A Deep Perceptual Spatial-Audio Localization Metric
Pranay Manocha, Anurag Kumar, Buye Xu, Anjali Menon, Israel D. Gebru, Vamsi K. Ithapu, Paul Calamia
WASPAA 2021
Paper Full Video - CDPAM: Contrastive learning for perceptual audio similarity
Pranay Manocha, Zeyu Jin, Richard Zhang, Adam Finkelstein
ICASSP 2021 - Canada
Paper Github Full Video - 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
Paper Poster - Brain Classification and Segmentation of MR Brain Images
Tanvi Gupta, Pranay Manocha, Tapan Kumar Gandhi, R.K Gupta, B.K Panigrahi
Neurocomputing
Paper - 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)
Paper - 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
Paper