Digital Currency Group
Internet Investing
Learn about the possibilities & pitfalls of using the Internet as an investment tool. Online investors must be aware that high Internet traffic may affect their ability to access their account or transmit their orders. Also, they should be skeptical of stock advice and tips provided in chat rooms and should do their own research before acting on these tips.
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Publications
Accepted
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VaPar Synth - A Variational Parametric Model for Audio Synthesis
Krishna Subramani,
Preeti Rao
Alexandre D'Hooge
ICASSP 2020
Paper /
Code /
Audio Examples /
DOI /
BibTeX
We present VaPar Synth - a Variational Parametric Synthesizer for instrument note synthesis, which utilizes a conditional variational autoencoder trained on a source-filter inspired parametric representation.
We will be presenting our work virtually at ICASSP 2020! (Presentation Video)
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Energy-Weighted Multi-Band Novelty Functions for Onset Detection in Piano Music
Krishna Subramani,
Srivatsan Sridhar,
Rohit M A,
Preeti Rao
National Conference on Communications 2018
Paper /
DOI /
BibTeX
Propose the use of energy-based weighting of multi-band onset detection functions and the use of a new criterion for adapting the final peak-picking threshold to improve detection of soft onsets in the vicinity of loud notes. Also propose a grouping algorithm to reduce the detection of spurious onsets.
We presented our work at the conference as an oral presentation
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Generative Audio Synthesis with a Parametric Model
Krishna Subramani,
Alexandre D'Hooge,
Preeti Rao
ISMIR 2019 Late Breaking/Demo
Abstract /
Audio Examples /
BibTeX
Propose a parametric representation for audio corresponding more directly to its musical attributes such as pitch, dynamics and timbre. For more control over generation, we also propose the use of a conditional variational autoencoder which conditions the timbre on pitch.
We presented our work as a poster in the ISMIR 2019 Late Breaking/Demo session
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Submitted
Research Experience
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Variational Parametric Models for Audio Synthesis
Report /
Repository /
Review of Generative Models for Audio Synthesis
(Ongoing)My Master's thesis work on generative parametric models for audio synthesis.
I presented the work done by me so far as an oral presentation for the first stage defense of my Master's thesis
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Compression using Graph Signal Processing
Presentation /
Report /
Notebook Demonstration of the Code
Inspired by the authors work on compressing distributed data by modeling it as graphs, we decided to try out and extend the idea to a new dataset by performing outlier removal, data imputation and clipping, and were able to successfully compress it at a significantly faster rate(~8x speedup) than conventional techniques.
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Data Sonification using Granular Synthesis
Report /
Code Repository
Implemented a real-time granular synthesizer on Pure Data. Also ideated a scheme where the parameters of the synth could be controlled externally with data, thus 'sonifying' the data!
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Kuramoto Model and Oscillatory Networks
Image Recall
Implemented an image retrieval(memory recall) task using the Kuramoto Model. Extended this to try out graph coloring using Oscillatory Networks.
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