I am working as a Speech Scientist at Capio Inc. focussing on implementation of Auto-ML techniques for speech recognition models. I am a PhD. candidate at Carnegie Mellon University in the Department of Electrical and Computer Engineering, based off the Silicon Valley Campus. I graduated with an MS in Electrical and Computer Engineering from Carnegie Mellon University in 2011 and a B.E. in Electronics and Telecommunications in 2010 from the University of Pune, India. My past industry experiences includes an internships at Baidu Silicon Valley Artificial Intelligence Lab, and Lenovo Speech Labs. My research is focussed on the development and analysis of techniques that can be used to speed up hyper-parameter optimization, specifically for deep neural networks for tasks in speech recognition and image processing on various computing architectures.
Ph.D. in Electrical and Computer Engineering • January 2012 - Present
I am a Ph.D. Candidate in ECE. My research is focussed on hyper-parameter optimization strategies to build deep neural network (DNN) systems for speech recognition on embedded platforms.
I am currently working on methods to utilize learning curves from previously completed hyper-parameter configurations to predict the performance for a new hyper-parameter configuration.
M.S. in Electrical and Computer Engineering • August 2010 - December 2011
I have completed my M.S. in Electrical and Computer Engineering with focus on Signal Processing and Machine Learning
B.E. in Electronics and Telecommunication Engineering • August 2006 - May 2010
I have completed my B.E. in Electronics and Telecommunication Engineering with focus on Signal Processing and Embedded Systems.
Speech Scientist• June 2017 - Present
I am working as a speech scientist on the following:
Acceleration of optimization of neural network-based speech recognition models.
Rapid development of Speech recognition models for multiple low-resource languages.
Integration of Automated hyper-parameter optimization techniques for ASR model combination.
Exploratory work on online speaker change detection.
Integration of dynamic word addition to online speech recognition.
Integration of automated hyper-parameter optimization for decoder hyper-parameters.
Research Intern• May 2016 - August 2016
During the course of my internship, I worked on importance sampling-based data sampling techniques to improve training time for speech recognition.
I also worked on improving the in-house speech recognition toolkit for better visualization of results.
I implemented a framework to allow different data selection strategies for deep learning.
Research Intern • October 2013 - May 2014
As a research intern at Lenovo Speech Labs, I worked on the development of an Android SDK that could allow developers to enable multi-modal interaction (speech and touch) within their applications.
I am a co-inventor in three patents that have resulted from this work.