Technical Background

Technical Proficiency 

Python

Matlab

C/C++

HTML

Javascript

R

JUCE

Max MSP

Flask

Numpy

Scipy

Tensorflow

1e0a Becomes A Drum Machine (Guthman Fair 2023)

Created an interactive demo for my thesis research by building a drum machine that recommends pattern strings for you based on an input pattern string. It was a fun tool to demo at the Guthman fair, where the attendees got to compose fun drum grooves and jam along with my synthesizers. 

Music De-noising system 

DSP for Music Analysis and Synthesis Course Project (May 2023)

Implemented a two-step wiener filter noise reduction system in Matlab, leading a group that achieved a notable mean +2 dB improvement in signal-to-noise ratio (SNR) compared to the baseline system. 

Muti-Pass Effects Plugin using JUCE

Audio Software Engineering Course Project (May 2022)

Created a real-time C++ JUCE plugin host tailored specifically for multi-band processing, allowing users to effortlessly split stems into frequency bands and apply a diverse range of third-party plugins to each band. Designed a low-complexity multi-band filter with flat group delay response

Voice Multi-Effect API

Audio Software Engineering 

Real-Time AudioFx API in C++ 11, that can be used to apply a variety of effects to a vocal audio signal. The ffects include: CombFilter (FIR, IIR), Vibrato, Tremolo, and Reverb. Reverb implementation is a OLA fast convolution that achieved an average run-time of 5.6s on a 3-minute track with an Impulse Response of 3s

StressBeat

Brain Music Interfaces Course Project (Dec 2021)

Designed and developed a drum machine interface controlled by heart rate and muscle activity. The tempo is set by the user tapping their finger; the user’s real-time changes in heart rate adjust the micro-timing of individual components in the drum groove.

Melograph

Audio Content Analysis Class Project (Dec 2021) 

Created an educational web application that takes input audio signals containing melodies and generates visually intuitive graph representations, revealing the note-to-note relationships and structural elements in a concise and insightful manner.

'1e0a': A Computational Approach to Rhythm Training

Under the guidance of Dr. Ranjani H.G.

In this work we develop an automated learning application based on feedback from a user to promote the learning of basic rhythmic patterns. The application is built to mimic a teacher-student relationship where, the subsequent levels of pattern complexity are generated based on the performance measured on the current pattern played by the user.  The web application built for the project serves as a data collection tool to test my rhythm education hypothesis, kindly do register and help me in my research.

Sound Event Localization Using an End to End Deep Convolutional Neural Network

Under the guidance of Dr. Ajey S.N.R.

As part of my final year capstone project, I am working on implementing a novel end-to-end deep convolutional neural network architecture operating on multi-channel raw audio data to localize multiple simultaneously active acoustic sources in space. As proposed by Dr. Harshavardhan Sundar.

Audio Sense

Audio Sense is an Alexa game skill that makes use of Alexa Conversations. It aims to help and train players to cope with Auditory Hypersensitivity and distractive environmental sounds. The skill sets up a game environment that can span over multiple settings and levels. The goal of the game is for the player to zone out auditory disturbances in a given environment to discern only the necessary and valid information from the same.

MELODY SEQUENCER

A web-based musical instrument with a mind of its own. 

Uses Google's Magenta.js trained machine learning models to generate it's own sequence of melodies and randomise drum grooves.

Copy of SIH 2020(MK91)

[(MK91) SIH FINALS PROJECT] SUB-CENTRE FOCUSED HEALTH CARE SYSTEM FOR THE GOVT. OF UTTARAKHAND

There's acute shortage of accessible health care in smaller towns and remote villages of Uttarakhand. We developed a system solution to this problem with the following points focussed upon :

CRACK ANALYSIS IN BRIDGES AND OTHER STRUCTURES

This project is a mechanism based on IOT-automation that can detect cracks in structures (Living Spaces and Flyovers). The system gathers information from the magnitude of vibrations produced by the structure using vibration sensors which relay information to a database for further data collection, analysis, and future reference. After the gathered data is analysed, the concerned authorities are notified about the condition of the structure.

COMMUNITY

Course_Plan.pdf

PESU IO

PESU I/O Courses is a first-ever peer-peer learning system, where students interact with Subject Matter Experts of a plethora of domains ranging from Co-Curriculars to Extra-Curriculars. It implements the concept of a flipped classroom, where the juniors gain insights and aspire to be like the SME, and the SMEs have an intellectually stimulating, worthwhile experience.

I was a Subject Matter Expert (SME) for the certified course 'An Engineer's Guide To Music Technology'. I formulated the whole course material and guided a class of 40 students over 4 weeks (8 sessions) with group discussions and assignments. Along with mentorship for a final project.