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Become a sponsor to David Zurow

@daanzu

David Zurow

daanzu

I develop free, open source, cross-platform software for better controlling computers by voice. Primarily, I'm building kaldi-active-grammar: a library that packages and extends the Kaldi speech recognition engine for real-time command & control with many complex grammars. I'm using it to write a backend for Dragonfly/Caster, which exemplify this interaction approach. However, kaldi-active-grammar isn't tightly coupled to them, and can be used by other frontends/frameworks as well.

I've been coding entirely by voice for 5+ years, and find major (commercial) offerings sorely lacking. They are designed mostly for generic prose dictation. Their voice commands are limited and verbose, making them frustrating and fatiguing for power users. They support certain languages/dialects/accents, but if you don't sufficiently match them, there's not much you can do about it. They are inflexible, closed systems.

I want to leverage state-of-the-art speech recognition technology to empower individual users to help themselves as they best know how. If you value this work and want to encourage development, please consider supporting me. Thanks!

Please message me if you would like to have your name listed as a backer, or any other reward.

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Past sponsors 22
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Featured work

  1. daanzu/kaldi-active-grammar

    Python Kaldi speech recognition with grammars that can be set active/inactive dynamically at decode-time

    Python 338
  2. daanzu/dragonfly

    Speech recognition framework allowing powerful Python-based scripting and extension of Dragon NaturallySpeaking (DNS), Windows Speech Recognition (WSR) and CMU Pocket Sphinx

    Python 4
  3. daanzu/deepspeech-websocket-server

    Server & client for DeepSpeech using WebSockets for real-time speech recognition in separate environments

    Python 101

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Your questions, issues, and feature requests will receive priority attention. (Though I intend to attend to all feedback regardless of sponsorship.)

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Optionally, I will train a custom personal speech recognition model for you, for optimal accuracy, instead of using a generic English model. (You'll need to provide me with your audio, and this is highly experimental at the moment. Be a part of the cutting edge!)

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