Showing 4 open source projects for "automatic volume mixer"

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  • 1
    EasyVoice

    EasyVoice

    Open source text-to-speech tool, supports extra-long text

    easyVoice is an open-source text-to-speech platform aimed at turning long-form text and novels into high-quality audio, with a strong focus on usability and scalability. It provides a web interface where users can paste or upload large texts and generate speech and subtitles in a single workflow, even for works exceeding 100,000 characters. The system supports multi-role voice acting, letting users assign different neural voices to different characters or narrative roles and configure...
    Downloads: 1 This Week
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  • 2
    Vald

    Vald

    Vald. A Highly Scalable Distributed Vector Search Engine

    ...Which can be configured to fit the gRPC interface. Horizontal scalable on memory and cpu for your demand. Vald supports to auto backup feature using Object Storage or Persistent Volume which enables disaster recovery.
    Downloads: 0 This Week
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  • 3
    XZVoice

    XZVoice

    Free and open source text-to-speech software

    ...The high-fidelity and flexible configuration of speech synthesis products opens up the closed loop of human-computer interaction and enables applications to sound realistically. A variety of timbres are available, and functions such as adjusting speech rate, intonation, and volume are provided. Technically, multi-level rhythmic pauses are taken into account to achieve the purpose of natural synthesizing rhythm, and comprehensively use acoustic parameters and linguistic parameters to establish multiple automatic prediction models based on deep learning. Using massive audio data to train the pronunciation model, the synthetic sound is real, full, cadenced, and expressive, and the MOS score has reached the professional level in the industry.
    Downloads: 0 This Week
    Last Update:
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  • 4

    Devanagari OCR

    Devanagari Optical Character Recognition, Annotation tool

    ...To cite this work, please use: "Devanagari OCR using a recognition driven segmentation framework and stochastic language models", Suryaprakash Kompalli, Srirangaraj Setlur, Venu Govindaraju, IJDAR, 2009, Volume: 12, Pg.: 123–138
    Downloads: 1 This Week
    Last Update:
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