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README.md

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+---
+license: cc-by-nc-4.0
+language:
+  - en
+library_name: ctrlspeech
+pipeline_tag: text-to-speech
+tags:
+  - text-to-speech
+  - speech-synthesis
+  - prosody-control
+  - controllable-tts
+  - flow-matching
+---
+
+# CtrlSpeech
+
+Checkpoints for **CtrlSpeech** — expressive speech synthesis with coarse-to-fine
+latent control. Code, CLI and interactive demo:
+**https://github.com/zszheng147/CtrlSpeech**
+
+CtrlSpeech is a zero-shot TTS model you can steer after generating. It exposes
+the pitch contour, loudness contour and phoneme boundaries of any utterance,
+lets you edit one of them, and resynthesises following the edit while leaving
+the others alone. Prosody is conditioned **per phoneme token**, so a single word
+can be stretched while the rest of the sentence keeps its timing.
+
+## Contents
+
+| Path | Params | Prosody control | Notes |
+|---|---|---|---|
+| `control-600m/` | 692 M | pitch · loudness · duration | Default |
+| `control-150m/` | 150 M | pitch · loudness · duration | Smaller |
+| `base-600m/` | 689 M | — | Ablation baseline, no control |
+| `base-150m/` | 148 M | — | Ablation baseline, no control |
+| `svae/` | — | — | SVAE (DAC + BigVGAN) 16 kHz codec, 40 Hz latents |
+| `shared/campplus.onnx` | — | — | CAM++ speaker embedding |
+| `shared/vocab.json` | — | — | Phoneme vocabulary (ARPAbet) |
+
+Each model folder holds `model.safetensors`, a training-free `config.yaml`, and
+the `qwen_config.json` describing the AR backbone architecture. The fine-tuned
+backbone weights are inside the checkpoint; no Qwen weights are redistributed
+and none are downloaded at load time.
+
+## Usage
+
+```bash
+pip install git+https://github.com/zszheng147/CtrlSpeech
+```
+
+```python
+from ctrlspeech import CtrlSpeech, shift_pitch_semitones
+
+tts = CtrlSpeech.from_pretrained("control-600m")     # downloads on first use
+baseline = tts.from_audio("clip.wav", "the transcript of that clip")
+tts.regenerate(baseline, pitch=shift_pitch_semitones(baseline.gen_f0, 5)) \
+   .save("higher.wav")
+```
+
+Duration editing and adopting your own recording require
+[Montreal Forced Aligner](https://montreal-forced-aligner.readthedocs.io) with
+the `english_us_arpa` acoustic model and dictionary.
+
+## Control representation
+
+Analysis runs at 100 frames/s (16 kHz, hop 160).
+
+- **Pitch** — 128 mel-spaced bins; bin 0 is unvoiced.
+- **Loudness** — 64 A-weighted dB bins, about 1.05 bins per dB.
+- **Duration** — per-phoneme frame counts, at most 191 frames (1.91 s) per
+  phoneme; an edited timeline is capped at 2001 frames (20 s).
+
+## Training data
+
+English speech from Emilia, GigaSpeech, LibriTTS / LibriTTS-R, HiFi-TTS and
+LibriLight, with forced-aligned ARPAbet phoneme annotations.
+
+## Licence and intended use
+
+**CC BY-NC 4.0 — non-commercial.** The training mix includes Emilia, which is
+distributed under CC BY-NC 4.0, so these weights inherit that restriction. The
+source code is MIT.
+
+These models clone a speaker's voice from a few seconds of reference audio.
+Only use recordings you have the right to use, disclose synthetic speech as
+synthetic, and do not use this to impersonate anyone without their consent.