Showing 4 open source projects for ".java"

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  • 1
    ASRT Speech Recognition

    ASRT Speech Recognition

    A Deep-Learning-Based Chinese Speech Recognition System

    ASRT is an end-to-end deep-learning Chinese ASR system built with TensorFlow/Keras, using convolution + CTC and a Max-Entropy HMM language model. It provides a REST/gRPC server backend and client SDKs in multiple languages (Python, Java, Go, Windows). Notably lightweight, it performs well without needing GPU acceleration and runs across platforms, targeting developers and researchers building Chinese voice interfaces.
    Downloads: 0 This Week
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  • 2
    InproTK

    InproTK

    An Incremental Spoken Dialogue Processing Toolkit

    InproTK is an Incremental Spoken Dialogue Processing Toolkit, that is, a toolkit to help you build dialogue systems that listen and talk incrementally, allowing for advanced interactional behaviour. Please see our Wiki for more information: http://sourceforge.net/p/inprotk/wiki/
    Downloads: 1 This Week
    Last Update:
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  • 3
    Voice Conference Manager uses VoiceXML and CCXML to control speech recognition, text to speech, and voice biometrics for a telephone conference service. Say the names or numbers of people and VCM places them into the call. Can be hosted on public servers
    Downloads: 0 This Week
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  • 4
    Provides a voice interface for applications via a plug in system. Allows the inclusion of voice recognition in an application with a minimum of effort.
    Downloads: 0 This Week
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  • SoftCo: Enterprise Invoice and P2P Automation Software Icon
    SoftCo: Enterprise Invoice and P2P Automation Software

    For companies that process over 20,000 invoices per year

    SoftCo Accounts Payable Automation processes all PO and non-PO supplier invoices electronically from capture and matching through to invoice approval and query management. SoftCoAP delivers unparalleled touchless automation by embedding AI across matching, coding, routing, and exception handling to minimize the number of supplier invoices requiring manual intervention. The result is 89% processing savings, supported by a context-aware AI Assistant that helps users understand exceptions, answer questions, and take the right action faster.
    Learn More
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