vjbytes102

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.

Gana-

Node Js music streaming web app

Generative-AI-with-LLMs

In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.

Intro-to-Data-Science

issue-guidelines

A set of guidelines for submitting issues and pull requests on projects

Llama-2

All the projects related to Llama

llm-course

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

ML-Course-Notes

🎓 Sharing course notes on all topics related to machine learning, NLP, and AI.

MTB_scoring

Code for scoring Mobile Toolbox measures

openwillis

Python library for digital measurement of health

vjbytes102/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.

vjbytes102/Gana-

Node Js music streaming web app

vjbytes102/Generative-AI-with-LLMs

In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.

vjbytes102/Intro-to-Data-Science

vjbytes102/issue-guidelines

A set of guidelines for submitting issues and pull requests on projects

vjbytes102/Llama-2

All the projects related to Llama

vjbytes102/llm-course

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

vjbytes102/ML-Course-Notes

🎓 Sharing course notes on all topics related to machine learning, NLP, and AI.

vjbytes102/MTB_scoring

Code for scoring Mobile Toolbox measures

vjbytes102/openwillis

Python library for digital measurement of health

vjbytes102/restrobooking

php/mysql

vjbytes102/Spring-Rest-Webservice

vjbytes102/spring-security-login

Spring MVC framework

vjbytes102/StreamingSpeakerDiarization

Lightweight python library for speaker diarization in real time implemented in pytorch

vjbytes102/whisperX

WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)

vjbytes102/willisapi_client

A Python client for willisAPI