3 रिपॉजिटरी
Tools for correcting natural language text within source files.
Distinct from Natural Language Interfaces: Focuses on text formatting and correction rather than command-line interfaces.
Explore 3 awesome GitHub repositories matching development tools & productivity · Natural Language Formatters. Refine with filters or upvote what's useful.
This project is a comprehensive, curated directory of static analysis, linting, and security scanning utilities. It serves as a central resource for developers to discover, compare, and select tools based on specific programming languages, licensing models, and integration requirements. The directory distinguishes itself by providing deep metadata for each listed utility, including community-driven popularity rankings, maintenance status, and deployment methods. By aggregating these tools into a single searchable index, it enables teams to identify solutions for enforcing coding standards, ma
Corrects spacing, word usage, and punctuation errors in natural language text to improve documentation quality.
KittenTTS is a neural text-to-speech engine and text-to-audio synthesis tool that converts written text into spoken audio using lightweight neural network models. It functions as both a speech synthesizer and an audio file generator, producing spoken audio for offline playback. The system includes a text normalization processor that expands numbers and abbreviations into full spoken words to improve the naturalness of the synthesized speech. It supports diverse voice options and provides the ability to adjust playback speed.
Prepares raw text by expanding abbreviations and numbers to ensure high-quality synthesized speech.
Humanizer is a .NET natural language formatter and string manipulation library designed to convert technical identifiers, numbers, and dates into grammatically correct, human-readable text. It functions as a pluralization engine, localization utility, and case conversion tool for the .NET ecosystem. The library provides specialized capabilities for transforming programming conventions like PascalCase or snake_case into readable sentences and vice versa. It distinguishes itself by handling irregular and uncountable English words during pluralization and singularization, and by applying culture
Transforms numbers, dates, and time durations into human-readable words and relative descriptions.