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How to study how a TTS model was distilled with Paradee

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

Short answer: Read the paper at arxiv.org/abs/2610.06817 and the How it works section of the README; then open the training/ folder and the training/data/ sentences, which come from WikiText-103; review how the text side, decoder and assembly steps are split, noting that the decoder is trained with spectrogram losses and then adversarial training. All steps.

Who it is forA researcher or student who wants to learn how a large TTS model was compressed into a small one.

The problemDistillation steps for speech models are rarely laid out end to end with code that runs on a single machine.

The outcomeA working understanding of the corpus, text-side training, decoder training and assembly steps, plus a local run of one stage.

What you need first

  • 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)

Steps

  1. Read the paper at arxiv.org/abs/2610.06817 and the How it works section of the README.
  2. Open the training/ folder and the training/data/ sentences, which come from WikiText-103.
  3. Review how the text side, decoder and assembly steps are split, noting that the decoder is trained with spectrogram losses and then adversarial training.
  4. Run one stage from training/ on your laptop, since the README says the code runs on one laptop.

Prompt for your agent

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.

Caveat. The paper describes version 1.0 and the 1.1 decoder head is only summarized in the README, so the code for 1.1 may differ from the paper's method.

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Using the Deduped MCP, get the setup steps for sahilmahendrakar/paradee and "Study how a TTS model was distilled"

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