Search Results for "data quality cleansing"

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.

...Version 1.3.0 adds offline punctuation and capitalization: periods, commas, question marks and capital letters appear automatically as you dictate (Russian and English via neural models, basic rules for 30+ other languages). Designed with privacy as a top priority, Scribe works completely offline. Your voice data never leaves your computer. Powered by the Vosk engine, it supports multiple languages and provides high-quality recognition without an internet connection. Runs on Windows and Linux. Scribe is the perfect tool for anyone looking to boost productivity, improve accessibility, or simply interact with their computer in a new, hands-free way. ...

Open source speech models for Julius speech decoder. Its aim is to give access a wider community of speech recognition enthusiasts to quality models, which they can use in their own projects on different OS platforms (Unix, Windows, etc...) All of the models are based on HTK modelling software and data sets available freely on the Internet.

Speechalyzer: a tool for the daily work of a 'speech worker' It is optimized to process large speech data sets with respect to transcription, labeling and annotation. It is implemented as a client server based framework in Java and interfaces software for speech recognition, synthesis, speech classification and quality evaluation. The application is mainly the processing of training data for speech recognition and classification models and performing benchmarking tests on speech-to-text, text-to-speech and speech classification software systems.