Showing 5 open source projects for "free java swing component"

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  • 1
    Intelligent Keyword Miner

    Intelligent Keyword Miner

    Intelligent SEO keyword miner and predicing tool

    THIS IS A NETBEANS 8.02 PROJECT ENGLISH ONLY This program was made to help me with the patent research. It simply generates the search keywords, based on your upvotes or a downvotes of the input parameters. It can accept a text or URL (text takes a prescedence over the URL). If you input URL, it goes to a page, and learns its text from HTML format. This program is intelligent as it predicts what you may want to search next, based on your personal trends. After searching the...
    Downloads: 0 This Week
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  • 2

    Bermuda Text-to-Speech

    This project includes basic NLP and DSP techniques for Text-to-Speech

    See TTS demo at: http://rslp.racai.ro/index.php?page=tts This is an entirely written in JAVA project which includes a set of tools and methods designed to enable Multilingual Text-to-Speech (TTS) synthesis. We currently support English and Romanian but we will soon train more models and make them available for download. If you want to read more about our other NLP and TTS tools check out http://nlptools.racai.ro.
    Downloads: 0 This Week
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  • 3
    Open Pandora's Box

    Open Pandora's Box

    Pandora is an artificial intelligent web based bot

    Pandora is an artificial intelligent web based bot written in Java. Pandora is a component based AI architecture including, database memory, XML, voice, voice rec, chat, IRC, HTTP, Wiktionary, Freebase, consciousness, language, GUI, applet, web, jsp, Android
    Downloads: 0 This Week
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  • 4
    KeplerWeka adds the functionality of the open-source machine learning and data mining workbench WEKA to the free and open-source, scientific workflow application, Kepler.
    Downloads: 0 This Week
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  • 5
    Text annotation application (Tapp) is a stand alone software component that facilitates the quick annotation of text files for the purpose of creating labelled data for training, testing, and deploying machine learning models
    Downloads: 0 This Week
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