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NVIDIA/waveglow

0
View on GitHub↗
2,337 stars·536 forks·Python·BSD-3-Clause·13 views

Waveglow

A Flow-based Generative Network for Speech Synthesis

Features

  • Speech Synthesis - Flow-based network for fast and high-quality audio generation.
  • Acoustic User Interface - Flow-based network for speech synthesis.
  • Acoustic User Interfaces - Flow-based generative network for speech synthesis.
  • Speech Generation and Recognition - Listed in the “Speech Generation and Recognition” section of the The Incredible Pytorch awesome list.

Star history

Star history chart for nvidia/waveglowStar history chart for nvidia/waveglow

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with Waveglow

These projects share indexed features with Waveglow. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • lawl/noisetorchlawl avatar

    lawl/NoiseTorch

    21View on GitHub↗

    Project dead (security breach)

    View on GitHub↗21
  • belangeo/pyobelangeo avatar

    belangeo/pyo

    1,416View on GitHub↗
    Pythonaudiocdsp
    View on GitHub↗1,416
  • coqui-ai/ttscoqui-ai avatar

    coqui-ai/TTS

    45,568View on GitHub↗

    This project is a deep learning text-to-speech toolkit used for training and deploying neural speech synthesis models. It provides a comprehensive framework for converting written text into spoken audio, utilizing neural vocoders to transform synthesized spectrograms into high-fidelity audio waveforms. The toolkit includes a voice cloning system that replicates specific human voices by extracting speaker embeddings from short audio samples. It also supports multi-speaker audio synthesis, allowing the generation of speech across different vocal identities using specialized model architectures.

    Pythondeep-learningglow-ttshifigan
    View on GitHub↗45,568
  • magenta/ddspmagenta avatar

    magenta/ddsp

    3,300View on GitHub↗

    DDSP: Differentiable Digital Signal Processing

    Python
    View on GitHub↗3,300
Compare all 14 related projects→

Frequently asked questions

What does nvidia/waveglow do?

A Flow-based Generative Network for Speech Synthesis

What are the main features of nvidia/waveglow?

The main features of nvidia/waveglow are: Speech Synthesis, Acoustic User Interface, Acoustic User Interfaces, Speech Generation and Recognition.

Which projects share features with nvidia/waveglow?

Projects with overlapping indexed features include: mozilla/deepspeech — DeepSpeech is an open-source speech-to-text framework and machine learning engine designed to convert spoken audio… belangeo/pyo. coqui-ai/tts — This project is a deep learning text-to-speech toolkit used for training and deploying neural speech synthesis models.… lawl/noisetorch — Project dead (security breach). magenta/ddsp — DDSP: Differentiable Digital Signal Processing. mycroftai/mycroft-core — Mycroft Core is an open-source voice assistant platform that processes spoken commands and runs modular skills for…