A project to build an AI voice assistant using Python . The Voice assistant interacts with the humans to perform basic tasks.

Last update: Oct 30, 2021

Overview

AI_Personal_Voice_Assistant_Using_Python

A project to build an AI voice assistant using Python . The Voice assistant interacts with the humans to perform basic tasks.

Libraries required to be installed using Pip Command:

speech_recognition as sr
pyttsx3
pywhatkit
datetime
wikipedia
pyjokes
os
random
webbrowser

Owner

Chumui Tripura

👋 Hi, I’m @Chumuitripura45.I’m interested in Computer Vision and Deep Learning.Currently learning Java, Mobile app development. I’m looking to collaborate on..

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A project to build an AI voice assistant using Python . The Voice assistant interacts with the humans to perform basic tasks.

Related tags

Overview

AI_Personal_Voice_Assistant_Using_Python

Libraries required to be installed using Pip Command:

Owner

Chumui Tripura

Funnels: Exact maximum likelihood with dimensionality reduction.

A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.

img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation

D2LV: A Data-Driven and Local-Verification Approach for Image Copy Detection

Code and data for ACL2021 paper Cross-Lingual Abstractive Summarization with Limited Parallel Resources.

How to train a CNN to 99% accuracy on MNIST in less than a second on a laptop

"Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices", official implementation

Ludwig is a toolbox that allows to train and evaluate deep learning models without the need to write code.

MRQy is a quality assurance and checking tool for quantitative assessment of magnetic resonance imaging (MRI) data.

Human Pose estimation with TensorFlow framework

Self-driving car env with PPO algorithm from stable baseline3

Code for the ECCV2020 paper "A Differentiable Recurrent Surface for Asynchronous Event-Based Data"

This repo contains code to reproduce all experiments in Equivariant Neural Rendering

Tensorflow 2 implementation of the paper: Learning and Evaluating Representations for Deep One-class Classification published at ICLR 2021

Unofficial implementation of "Coordinate Attention for Efficient Mobile Network Design"

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