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PiVo-1.4M: 1.4M-parameter English TTS that runs offline on CPU

AIModelScope releases PiVo-1.4M, an English text-to-speech model with 1.4M parameters and a built-in vocoder that generates 16 kHz mono speech. It runs offline on CPU using NumPy and ONNX Runtime without PyTorch, and reaches a 0.532% WER on its held-out test set, a measure of intelligibility rather than naturalness.
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English TTS in just 1.4M parameters, vocoder included. PiVo-1.4M runs offline on a CPU with NumPy and ONNX Runtime, without PyTorch.
🤖 https://modelscope.ai/models/empero-ai/PiVo-1.4M

🪶 1.4M parameters, vocoder included: Generates 16 kHz mono speech with a compact acoustic model and FARGAN-derived vocoder.
🖥️ Built for local, offline use: Generate with either English voice, Pi or Vo, directly on CPU and begin playback in 10 ms audio frames after text encoding.
🗣️ Words come through clearly: PiVo reaches 0.532% WER on its held-out test set. The authors note that this measures intelligibility, not general English quality or naturalness.
🔤 Predictable English pronunciation: It expands numbers, currencies, ordinals, and ISO dates, while unsupported words raise a clear error instead of silently guessing.
📜 Code and acoustic weights are Apache-2.0. The FARGAN-derived vocoder uses Xiph/Opus BSD terms, and the pronunciation dictionary retains its CMU license.

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Original title: English TTS in just 1.4M parameters, vocoder included. PiVo-1.4M runs offline on a CPU with NumPy and ONNX Runtime, without PyTorch.