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🚀 About Me

I'm an Electrical engineering masters student at the University of Southern California with Research experience in Speech processing and enhancement using machine learning algorithms. I have worked extensively on Automatic speech recognition systems in challenging conditions such as noisy and reverberent environment.

I have worked on various NLP and Computer Vision projects, machine learning being at the core of all these projects.

🛠 Skills

Languages

Python • Shell Scripting • Java • JavaScript • C# • SQL

Technologies / Libraries

Kaldi • PyTorch • TensorFlow • Scikit-Learn • Numpy • Pandas • AWS • GitHub • Web Services • Spring MVC • MVVM • CUDA

🔗 Links

portfolio linkedin twitter

Other Common Github Profile Sections

👩‍💻 I'm currently working on Adversarial attack on Automatic speech recognition systems and conversation AI with multiple speakers

🧠 I'm currently learning Federated learning

👯‍♀️ I'm looking to collaborate on anythng in conversation AI

💬 Ask me about speech recognition

📫 How to reach me [email protected]

⚡️ Fun fact, I'm a musician

Anirudh Sreeram's Projects

advanced_computer_vision icon advanced_computer_vision

This Repo contains implementation of various classical Image processing algorithms and Computer vision based algorithms that are used to perform Image classification and detection

algorithms icon algorithms

Basic algorithms and data structures required to perform programming tasks

denoiser icon denoiser

Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.

federated-learning icon federated-learning

A PyTorch Implementation of Federated Learning http://doi.org/10.5281/zenodo.4321561

genderpredictionapp icon genderpredictionapp

This project contains the codes for training a naive bayesian based gender detection model, coupled with a python based application to use the trained models

lm-bff icon lm-bff

ACL'2021: LM-BFF: Better Few-shot Fine-tuning of Language Models

mbse_ai_se icon mbse_ai_se

Reinforcement learning tutorial codes and system engineering stuff

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