Showing 2 open source projects for "sourcecode for network monitoring system"

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  • A privacy-first API that predicts global consumer preferences Icon
    A privacy-first API that predicts global consumer preferences

    Qloo AI adds value to a wide range of Fortune 500 companies in the media, technology, CPG, hospitality, and automotive sectors.

    Through our API, we provide contextualized personalization and insights based on a deep understanding of consumer behavior and more than 575 million people, places, and things.
    Learn More
  • Job Evaluation and Talent Management Software Icon
    Job Evaluation and Talent Management Software

    For human resources departments in search of a tool to manage time, expenses, leave, documents, recruitment, and onboarding

    Encompassing Visions (ENCV), industry-leading job evaluation and pay equity software, is the best choice for organizations requiring transparent, comprehensive, and objective Job Evaluation software designed to help them ensure equal pay for work of equal value.
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  • 1
    WhisperLive

    WhisperLive

    A nearly-live implementation of OpenAI's Whisper

    WhisperLive is a “nearly live” implementation of OpenAI’s Whisper model focused on real-time transcription. It runs as a server–client system in which the server hosts a Whisper backend and clients stream audio to be transcribed with very low delay. The project supports multiple inference backends, including Faster-Whisper, NVIDIA TensorRT, and OpenVINO, allowing you to target GPUs and different CPU architectures efficiently. It can handle microphone input, pre-recorded audio files, and network streams such as RTSP and HLS, making it flexible for live events, monitoring, or accessibility workflows. ...
    Downloads: 10 This Week
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  • 2
    Transformer TTS

    Transformer TTS

    Implementation of a Transformer based neural network

    TransformerTTS is an implementation of a non-autoregressive Transformer-based neural network for text-to-speech, built with TensorFlow 2. It takes inspiration from architectures like FastSpeech, FastSpeech 2, FastPitch, and Transformer TTS, and extends them with its own aligner and forward models. The system separates alignment learning and acoustic modeling: an autoregressive Transformer is used as an aligner to extract phoneme-to-frame durations, while a non-autoregressive...
    Downloads: 0 This Week
    Last Update:
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