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ideasman42 avatar

ideasman42/nerd-dictation

0
View on GitHub↗
1,878 stars·159 forks·Python·GPL-3.0·3 views

Nerd Dictation

Nerd-dictation is a command-line utility that provides offline speech-to-text transcription and system-wide desktop automation. It functions as a local recognition engine, processing microphone audio streams directly on the host machine without requiring cloud connectivity or external network services.

The tool distinguishes itself by integrating transcription directly into the desktop environment through system-level input injection, which simulates keyboard events to type recognized speech into active application windows. It supports grammar-constrained decoding, allowing users to define specific vocabularies to improve transcription accuracy for technical domains. Additionally, the software includes a pipeline-based transformation system that enables users to execute custom scripts, perform numeric formatting, and trigger automated workflows based on recognized keywords.

The framework manages the entire dictation lifecycle, including start, stop, and pause signaling, while offering configuration options to balance resource consumption against processing performance. It is designed for use on Linux environments and provides a modular interface for audio capture and text processing.

Features

  • Speech-to-Text Converters - Converts spoken audio into written text using offline recognition models for system-wide dictation.
  • Desktop Dictation Utilities - Enables system-wide desktop automation by converting spoken audio into text and injecting it directly into active application windows as simulated keystrokes.
  • Offline - Provides local, offline speech-to-text transcription by processing microphone audio streams directly on the host machine without cloud connectivity.
  • Contextual Accuracy Improvements - Improves transcription precision for specialized domains by constraining the recognition vocabulary.
  • Grammar-Constrained Speech Processors - Provides a framework that restricts recognition to specific vocabularies and executes custom scripts based on spoken keywords.
  • Constrained Decoding - Limits the speech recognizer's search space using predefined vocabulary files to improve transcription accuracy for technical domains.
  • Custom Vocabularies - Allows users to define custom vocabularies to improve transcription accuracy for specialized technical domains.
  • Voice Dictation - Provides control over the transcription lifecycle, including start, stop, and pause signaling.
  • Keyboard and Mouse Input Simulations - Simulates keyboard input by injecting transcribed text into active windows across various display servers.
  • Voice-to-Text Input Automation - Automates system input by injecting transcribed speech directly into active applications as simulated keystrokes.
  • Linux Desktop Automation - Provides a system-level interface for Linux desktop automation via speech-to-text and keyboard injection.
  • Speech-to-Text Transformation Pipelines - Passes recognized text through custom scripts to perform formatting, keyword triggering, and numeric conversion.
  • Voice Command Mapping - Triggers automated workflows and custom scripts by mapping spoken keywords to system actions.
  • Process-Level Input Injectors - Injects transcribed text into active application windows by simulating keyboard events at the process level.

Star history

Star history chart for ideasman42/nerd-dictationStar history chart for ideasman42/nerd-dictation

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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Frequently asked questions

What does ideasman42/nerd-dictation do?

Nerd-dictation is a command-line utility that provides offline speech-to-text transcription and system-wide desktop automation. It functions as a local recognition engine, processing microphone audio streams directly on the host machine without requiring cloud connectivity or external network services.

What are the main features of ideasman42/nerd-dictation?

The main features of ideasman42/nerd-dictation are: Speech-to-Text Converters, Desktop Dictation Utilities, Offline, Contextual Accuracy Improvements, Grammar-Constrained Speech Processors, Constrained Decoding, Custom Vocabularies, Voice Dictation.

Which projects share features with ideasman42/nerd-dictation?

Projects with overlapping indexed features include: autokey/autokey — AutoKey is a Linux GUI macro manager and Python desktop automation tool. It functions as a background daemon that… beingpax/voiceink — VoiceInk is a system-wide speech-to-text dictation tool that converts spoken audio into text using local or cloud AI… agermanidis/autosub — Autosub is a command-line media processor and automatic subtitle generator that converts audio streams from video and… cmusphinx/pocketsphinx — PocketSphinx is an offline speech recognition engine that converts raw audio from files or live microphone streams… jordansissel/xdotool — xdotool is a command-line utility for X11 desktop automation that simulates keyboard and mouse input and manages… autoscrape-labs/pydoll — pydoll is a Chrome DevTools Protocol automation library and headless browser controller used for web data extraction…

Projects sharing features with Nerd Dictation

These projects share indexed features with Nerd Dictation. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
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    autokey/autokey

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    AutoKey is a Linux GUI macro manager and Python desktop automation tool. It functions as a background daemon that simulates keyboard and mouse events via the X11 protocol to automate interactions with graphical user interfaces. The software provides a Python scripting engine for executing stateful automation and a text expansion utility that replaces short abbreviations with predefined content or scripted actions in real time. It differentiates itself by combining low-level input simulation with the ability to manage global state and persistent variables across different scripts. The project

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    View on GitHub↗3,844
  • beingpax/voiceinkBeingpax avatar

    Beingpax/VoiceInk

    3,859View on GitHub↗

    VoiceInk is a system-wide speech-to-text dictation tool that converts spoken audio into text using local or cloud AI models. It functions as a local AI transcription engine and a context-aware voice assistant, allowing users to insert transcribed text directly into any active application on the operating system. The project distinguishes itself through the use of custom vocabulary management, which trains transcription engines to recognize industry-specific technical terms, professional terminology, and personal names. It further enhances output by using large language models to refine raw tr

    Swiftmacosmacos-appswift
    View on GitHub↗3,859
  • agermanidis/autosubagermanidis avatar

    agermanidis/autosub

    4,197View on GitHub↗

    Autosub is a command-line media processor and automatic subtitle generator that converts audio streams from video and audio files into timed text overlays. It functions as an AI speech-to-text converter that uses OpenAI Whisper to generate synchronized subtitles. The tool includes a language translation pipeline to convert transcribed speech into target languages, enabling multilingual video captioning. It manages the process from audio-stream extraction to the serialization of final subtitle files for local storage. The system covers audio-to-text transcription, time-stamped text mapping, a

    Python
    View on GitHub↗4,197
  • cmusphinx/pocketsphinxcmusphinx avatar

    cmusphinx/pocketsphinx

    4,276View on GitHub↗

    PocketSphinx is an offline speech recognition engine that converts raw audio from files or live microphone streams into written text without requiring a network connection. It functions as a speech-to-text library, a real-time transcription engine, and a voice command processor, capable of detecting and transcribing spoken commands from continuous audio streams with configurable acoustic and language models. The engine uses weighted finite-state transducers to represent acoustic, phonetic, and language models as a single search graph for efficient decoding. It employs fixed-point acoustic mod

    Ccpythonspeech-recognition
    View on GitHub↗4,276
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