Open Source C# Natural Language Processing (NLP) Tools

C# Natural Language Processing (NLP) Tools

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Browse free open source C# Natural Language Processing (NLP) Tools and projects below. Use the toggles on the left to filter open source C# Natural Language Processing (NLP) Tools by OS, license, language, programming language, and project status.

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  • 1
    Virastyar

    Virastyar

    Virastyar is an spell checker for low-resource languages

    Virastyar is a free and open-source (FOSS) spell checker. It stands upon the shoulders of many free/libre/open-source (FLOSS) libraries developed for processing low-resource languages, especially Persian and RTL languages Publications: Kashefi, O., Nasri, M., & Kanani, K. (2010). Towards Automatic Persian Spell Checking. SCICT. Kashefi, O., Sharifi, M., & Minaie, B. (2013). A novel string distance metric for ranking Persian respelling suggestions. Natural Language Engineering, 19(2), 259-284. Rasooli, M. S., Kahefi, O., & Minaei-Bidgoli, B. (2011). Effect of adaptive spell checking in Persian. In NLP-KE Contributors: Omid Kashefi Azadeh Zamanifar Masoumeh Mashaiekhi Meisam Pourafzal Reza Refaei Mohammad Hedayati Kamiar Kanani Mehrdad Senobari Sina Iravanin Mohammad Sadegh Rasooli Mohsen Hoseinalizadeh Mitra Nasri Alireza Dehlaghi Fatemeh Ahmadi Neda PourMorteza
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    Downloads: 198 This Week
    Last Update:
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  • 2
    Glint Translator
    Glint Translator is a high-performance, privacy-focused Windows application for real-time in-game and voice translation without interrupting gameplay. Powered by leading cloud and offline/local AI models including Google Gemini, OpenAI, xAI Grok, DeepL, Azure, and Ollama (Gemma, Qwen), it seamlessly translates 240+ languages with an intuitive, plug-and-play interface. Example: They speak German → you see Turkish They speak Turkish → you see German 🧠 AI Model Support Google Gemini: 2.5 Flash, 2.5 Pro OpenAI: GPT-4o, GPT-4 Turbo xAI: Grok Local/Offline (via Ollama Engine): Gemma, Qwen
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    Downloads: 22 This Week
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  • 3

    BibleNLP

    Natural Language Processing using The Holy Bible

    This project attempts to develop natural language processing routines as applied to a Bible text domain. Many common technologies (e.g., tokenization, Brill POS tagger) are used in conjunction with theoretical paradigms (e.g., hierarchical word definition trees, phrasal concordance).
    Downloads: 0 This Week
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  • 4
    BotSharp

    BotSharp

    AI Multi-Agent Framework in .NET

    Conversation as a platform (CaaP) is the future, so it's perfect that we're already offering the whole toolkits to our .NET developers using the BotSharp AI BOT Platform Builder to build a CaaP. It opens up as much learning power as possible for your own robots and precisely control every step of the AI processing pipeline. BotSharp is an open source machine learning framework for AI Bot platform builder. This project involves natural language understanding, computer vision and audio processing technologies, and aims to promote the development and application of intelligent robot assistants in information systems. Out-of-the-box machine learning algorithms allow ordinary programmers to develop artificial intelligence applications faster and easier. It's written in C# running on .Net Core that is full cross-platform framework. C# is a enterprise-grade programming language which is widely used to code business logic in information management-related system.
    Downloads: 0 This Week
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    CRFSharp

    CRFSharp

    CRFSharp is a .NET(C#) implementation of Conditional Random Field

    CRFSharp(aka CRF#) is a .NET(C#) implementation of Conditional Random Fields, an machine learning algorithm for learning from labeled sequences of examples. It is widely used in Natural Language Process (NLP) tasks, for example: word breaker, postagging, named entity recognized, query chunking and so on. CRF#'s mainly algorithm is the same as CRF++ written by Taku Kudo. It encodes model parameters by L-BFGS. Moreover, it has many significant improvement than CRF++, such as totally parallel encoding, optimizing memory usage and so on. Currently, when training corpus, compared with CRF++, CRF# can make full use of multi-core CPUs and only uses very low memory, and memory grow is very smoothly and slowly while amount of training corpus, tags increase. with multi-threads process, CRF# is more suitable for large data and tags training than CRF++ now. For example, in machine with 64GB, CRF# encodes model with more than 4.5 hundred million features quickly.
    Downloads: 0 This Week
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  • 6
    CSharpPOSTagger
    POS Tagger , Part of speech tagger, Hidden Markov Model , written with C#. Natural language Processing .
    Downloads: 0 This Week
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  • 7
    A WebCrawler for Natural Language Processing. This WebCrawler searches for monolingual (in a specified language) and bilingual, parallel text.
    Downloads: 0 This Week
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  • 8
    Recognizers-Text

    Recognizers-Text

    Recognition and resolution of numbers, units, date/time, etc.

    Recognizers-Text is a multilingual text recognition library that extracts structured information such as dates, numbers, and currency values from unstructured text.
    Downloads: 0 This Week
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  • 9
    Verbot Engine SDK
    Created by Conversive, the Verbot (Verbally Enhanced Software Robot) is based on more than 10 years of AI experience and development. Using XML and .NET architecture, the Verbots SDK allows you to create engaging interactive personalities.
    Downloads: 0 This Week
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  • 10
    neural network designer

    neural network designer

    a dbms for neural nets. Chatbots, DTrees, random forests, n-grams,...

    This project consists out of a windows based designer application and a library (that can run on multiple platforms, including android) together with several demo applications (including an MVC3 chatbot client and an android application). It is probably best compared to a database management system, but for neural networks instead of relational data. As such, the library is optimized for handling any type of data-size by using advanced streaming and caching algorithms. With the designer, you are able to create different types of decision trees, random forests, n-grams, pattern-matchers, conversational agents and all sorts of AI related algorithms. You can combine statistical approaches as well as pattern matchers or others. Do natural language processing, image or data analysis & interpretation,...
    Downloads: 0 This Week
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