Search Results for "chat application in python"

From ingesting data to exploring it, annotating it, and managing workflows. Diffgram is a single application that will improve your data labeling and bring all aspects of training data under a single roof. Diffgram is world’s first truly open source training data platform that focuses on giving its users an unlimited experience. This is aimed to reduce your data labeling bills and increase your Training Data Quality. Training Data is the art of supervising machines through data. This...

First, install Flashlight (using the 0.3 branch is required) with the ASR application. This repository includes recipes to reproduce the following research papers as well as pre-trained models. All results reproduction must use Flashlight <= 0.3.2 for exact reproducibility. At least one of LZMA, BZip2, or Z is required for LM compression with KenLM. It is highly recommended to build KenLM with position-independent code (-fPIC) enabled, to enable python compatibility.

The input pipeline must be prepared by the users. This code is aimed to provide the implementation for Coupled 3D Convolutional Neural Networks for audio-visual matching. Lip-reading can be a specific application for this work. Audio-visual recognition (AVR) has been considered as a solution for speech recognition tasks when the audio is corrupted, as well as a visual recognition method used for speaker verification in multi-speaker scenarios. The approach of AVR systems is to leverage the...

This simple pygtk application uses ffmpeg and arecord; to record sound Google's unofficial text to speech service; to convert sound to text The python subprocess module to run the text as a shell command. The text to speech service used by this application is unofficial, and this program should therefore be considered a complete hack.

This product recognizes oral commands and translates them to domotic orders for a domotic system. This product does not implement a domotic system. This product is an interface to be plugged to a domotic system. The speech recognition is done by an arduino UNO board and an EasyVR shield. Available oral commands are generated from a house description file in XML format. The oral commands have to be trained for a specific users. For this purpose 2 interfaces are provided: a command line...