Tacspeak - speech recognition for gaming

Fast, lightweight, modular - speech recognition for gaming

Introduction

Tacspeak has been designed specifically for recognising speech commands while playing games, particularly system resource and FPS hungry games!

Fast - typically on the order of 10-50ms, from detected speech end (VAD) to action.

Lightweight - it runs on CPU, with ~2GB RAM.

Modular - you can build your own set of voice commands for additional games, or modify existing ones.

Open source - you can modify any part of Tacspeak for yourself, and/or contribute back to the project and help build it as part of the community.

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Tacspeak is built atop the excellent Dragonfly speech recognition framework for Python.

• []Note: Tacspeak uses a modified version of Dragonfly located at jwebmeister/dragonfly.

  []Please see the Dragonfly docs for information on building grammars and rules (i.e. voice commands).

  []Please also see the existing examples of Tacspeak grammar modules.

  Also built atop the excellent Kaldi Active Grammar, which provides the Kaldi (also excellent) engine backend and model for Dragonfly.

  Requirements

  • []OS: Windows 10/11, 64-bit

    []~2GB+ disk space for model plus temporary storage and cache.

    []~2GB+ RAM.

    []Only supports English language speech recognition, as provided via Kaldi Active Grammar.

    Basic install - packaged executable

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    • []Download and install Microsoft Visual C++ Redistributable

      []Download the latest release on Nexusmods or latest release on GitHub, download the... (they are separate downloads and/or releases):

      []Tacspeak application .zip (includes .exe)

      []pre-trained model .zip (includes kaldi_model folder).

    []Extract the Tacspeak application .zip into a folder, and extract the Kaldi model .zip into the same folder. Check the following files exists:
    • []./tacspeak.exe

      []./tacspeak/user_settings.py

      []./tacspeak/grammar/_readyornot.py

      []./kaldi_model/Dictation.fst - if not you need to download and extract the pre-trained model

    • Run the executable Tacspeak/tacspeak.exe :)

      Usage

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      Run tacspeak.exe (or python ./cli.py