brijmohan

brijmohan's Stars

• NVIDIA/NeMo

  A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)

  Language:Python12.1k2062.3k2.5k

• NVIDIA/tacotron2

  Tacotron 2 - PyTorch implementation with faster-than-realtime inference

  Language:Jupyter Notebook5.1k1165621.4k

• espeak-ng/espeak-ng

  eSpeak NG is an open source speech synthesizer that supports more than hundred languages and accents.

  Language:C4.2k1011k900

• facebookresearch/nevergrad

  A Python toolbox for performing gradient-free optimization

  Language:Python4k58264354

• huggingface/speech-to-speech

  Speech To Speech: an effort for an open-sourced and modular GPT4-o

  Language:Python3.5k4487367

• tomgoldstein/loss-landscape

  Code for visualizing the loss landscape of neural nets

  Language:Python2.8k3341399

• JavierAntoran/Bayesian-Neural-Networks

  Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

  Language:Jupyter Notebook1.8k2824303

• pytorch/opacus

  Training PyTorch models with differential privacy

  Language:Jupyter Notebook1.7k46300345

• freewym/espresso

  Espresso: A Fast End-to-End Neural Speech Recognition Toolkit

  Language:Python9424254116

• jjery2243542/adaptive_voice_conversion

  Language:Python469113989

• StaticMania/portio-hugo

  Portio Hugo is a simple, minimal and responsive Portfolio Hugo Theme. Portio Hugo is well organized, well-formatted, and named accordingly so it’s easy to change any and all of the design. Portio is built with Bootstrap 4. You can customize it very easily to fit your needs.

  Language:HTML4511138290

• lfwa/carbontracker

  Track and predict the energy consumption and carbon footprint of training deep learning models.

  Language:Python397126430

• dilinwang820/Stein-Variational-Gradient-Descent

  code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"

  Language:Python385122120

• lochenchou/MOSNet

  Implementation of "MOSNet: Deep Learning based Objective Assessment for Voice Conversion"

  Language:Python346101062

• ksw0306/ClariNet

  A Pytorch Implementation of ClariNet

  Language:Python28923964

• jjery2243542/voice_conversion

  Language:Python24672267

• f0nzie/tikz_favorites

  collection of favorite TikZ graphics

  Language:TeX1929030

• sequitur-g2p/sequitur-g2p

  This is a github repository of the abandonware Sequitur G2P by Bisani & Ney

  Language:Python155114555

• cvqluu/Factorized-TDNN

  PyTorch implementation of the Factorized TDNN (TDNN-F) from "Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks" and Kaldi

  Language:Python1428534

• LaRiffle/collateral-learning

  Collateral Learning - Functional Encryption and Adversarial Training on partially encrypted networks

  Language:Jupyter Notebook75329

• idiap/pkwrap

  A pytorch wrapper for LF-MMI training and parallel training in Kaldi

  Language:Python73122212

• higuma/wav-audio-encoder-js

  Waveform Audio encoder for browsers

  Language:JavaScript703241

• Voice-Privacy-Challenge/Voice-Privacy-Challenge-2022

  Baseline Recipe for VoicePrivacy Challenge 2022: anonymization systems and evaluation software

  Language:Python6482115

• vvestman/pytorch-ivectors

  GPU accelerated implementation of i-vector extractor training using PyTorch. Requires Kaldi for feature extraction and UBM training. An example script is provided for VoxCeleb data.

  Language:Python642111

• Voice-Privacy-Challenge/Voice-Privacy-Challenge-2020

  Baseline Recipe for VoicePrivacy Challenge 2020: https://www.voiceprivacychallenge.org/vp2020/docs/VoicePrivacy_2020_Eval_Plan_v1_3.pdf

  Language:Shell5961226

• kan-bayashi/INTERSPEECH19_TUTORIAL

  Interspeech 2019 tutorial materials

  Language:Jupyter Notebook486211

• microsoft/INMT-lite

  Interactive Neural Machine Translation-lite (INMT-lite) is a framework to train and develop lite versions (.tflite) of models for neural machine translation (NMT) that can be run on embedded devices like mobile phones and tablets that have low computation power and space. The tflite models generated can be used to build the offline version of INMT mobile, a mobile version of INMT web.

  Language:C++451197

• deep-privacy/SA-toolkit

  SA-toolkit: Speaker speech anonymization toolkit in python

  Language:Python19411

• CRIStAL-Sigma/phd-thesis-template

  Template for PhD thesis using Tufte's style book

  Language:TeX9421

• deep-privacy/espnet

  End-to-End Speech Processing Toolkit

  Language:Python1300