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How to use Paradee: what you can do with it

What is Paradee? Paradee is a small 7.88M-parameter English text-to-speech model, distilled from Kokoro-82M, that speaks one voice and runs on CPU.

How do I use it? Run pip install git+https://github.com/sahilmahendrakar/paradee to install the package; then run python -m paradee "Paradee is a small voice that runs anywhere." -o hello.wav to generate a test file; in your Python code, import Paradee and SAMPLE_RATE from Paradee, create tts = Paradee(), and call tts("your text") to get the audio array. Full steps below.

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What do you want to do?

4 use cases

  • Add offline English speech to a Python app

    Install Paradee from GitHub and generate a WAV file from text on a CPU.

    View prompt
    Install the GitHub repo sahilmahendrakar/paradee with pip, then generate speech for the text <your sentence> and save it to <output.wav>. Expect a WAV file at 24 kHz that plays back as the spoken sentence. Verify the file exists and is longer than zero seconds before reporting success.

  • Ship a browser voice with no WebGPU or download

    Use Paradee's browser phonemizer and ONNX file to speak text inside a web page.

    View prompt
    Clone sahilmahendrakar/paradee, read web/misaki.js and the ONNX input spec in the README, then write a minimal browser page that speaks the text <your text>. Expect audio playback at 24 kHz with no WebGPU. Verify that the phoneme ids start and end with pad token 0 and total at most 512 before running inference.

  • Call the Paradee ONNX graph from any runtime

    Feed phoneme ids and speed into the ONNX graph and get 24 kHz audio back.

    View prompt
    Load the Paradee 1.1 int8 ONNX file from sahilmahendrakar/Paradee-8M-v1.1 with an ONNX runtime, build input_ids from phonemes in config.json with 0 pads, and run inference on the text <your phonemes>. Expect a float32 waveform at 24 kHz. Verify the output shape is [1, samples] and that the sample count is greater than zero.

  • Study how a TTS model was distilled

    Read the paper and training code to reproduce a teacher-student speech model on one laptop.

    View prompt
    Clone sahilmahendrakar/paradee, read the How it works section and the training/ folder, then summarize the four distillation steps and the parameter split for the text side and decoder. Expect a short summary with the 4.23M and 3.65M parameter counts. Verify that every number you report appears in the README or paper before finalizing.

Quick start with Paradee

  1. Check you have what it needs: Python with pip installed; Internet access for the first run, to download the 8.5 MB model and misaki's English dictionary data; Audio output support (soundfile is used in the README example).
  2. Open sahilmahendrakar/paradee on GitHub and read the README and license.
  3. Run pip install git+https://github.com/sahilmahendrakar/paradee to install the package.
  4. Run python -m paradee "Paradee is a small voice that runs anywhere." -o hello.wav to generate a test file.
  5. In your Python code, import Paradee and SAMPLE_RATE from Paradee, create tts = Paradee(), and call tts("your text") to get the audio array. (inferred, check the README)
  6. Write the array to a file with soundfile using sf.write("out.wav", audio, SAMPLE_RATE). (inferred, check the README)

These steps come from our top use case, Add offline English speech to a Python app, which also has a copy-paste agent prompt.

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About this repo

Requirements

  • Python with pip installed
  • Internet access for the first run, to download the 8.5 MB model and misaki's English dictionary data
  • Audio output support (soundfile is used in the README example)

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Questions about Paradee

What is Paradee?

Paradee is a small 7.88M-parameter English text-to-speech model, distilled from Kokoro-82M, that speaks one voice and runs on CPU. It is an open-source project on GitHub: https://github.com/sahilmahendrakar/paradee.

How do I use Paradee?

Run pip install git+https://github.com/sahilmahendrakar/paradee to install the package; then run python -m paradee "Paradee is a small voice that runs anywhere." -o hello.wav to generate a test file; in your Python code, import Paradee and SAMPLE_RATE from Paradee, create tts = Paradee(), and call tts("your text") to get the audio array. The use cases on this page give the full steps and a copy-paste agent prompt for each job.

Who is Paradee for?

Python developers and AI agents who need offline English speech output without a GPU or a large model download.

What can I do with Paradee?

4 use cases so far, for example: Add offline English speech to a Python app; Ship a browser voice with no WebGPU or download; Call the Paradee ONNX graph from any runtime. Each has steps and a copy-paste agent prompt.

What do I need to run Paradee?

Python with pip installed; Internet access for the first run, to download the 8.5 MB model and misaki's English dictionary data; Audio output support (soundfile is used in the README example).

What are alternatives to Paradee?

Other hot AI repos in Software and DevOps: Deep Infer, Harness2, Orca, Opencode, Graphify.

Is Paradee safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.