Model card: search keywords, voice table, FAQ, links

README.md

@@ -8,24 +8,47 @@ tags:
   - text-to-speech
   - tts
   - speech-synthesis
-  - onnx
-  - flow-matching
+  - neural-tts
+  - offline-tts
   - on-device
+  - edge-ai
   - edge
   - offline
   - cpu
+  - onnx
+  - onnxruntime
+  - lightweight
+  - small-model
+  - flow-matching
+  - vocos
+  - english
+  - raspberry-pi
+  - flockspeech
+  - accessibility
+  - screen-reader
+  - voice-assistant
+  - narration
 datasets:
   - keithito/lj_speech
 ---
 
-# Junco v0.1
+# Junco v0.1: tiny offline text-to-speech (TTS) for CPU
 
-**A small English text-to-speech model that runs offline on a CPU.**
+**A small, natural English text-to-speech model that runs offline on any CPU. 44 MB, no GPU, no cloud.**
 
 Junco is an 11.4M-parameter flow-matching TTS model from [Flock Speech](https://huggingface.co/flockspeech). It turns
 English text into natural 24 kHz speech on an ordinary CPU, faster than real time. It has no GPU, network or PyTorch
 dependency, and the full model is a 44 MB download.
 
+Junco is the clear, neutral **reading voice** of the Flock Speech family: a good fit for voice assistants, screen
+readers, notifications, narration and other on-device or edge AI speech output. Install it with
+`pip install flockspeech`.
+
+| Flock Speech voices | Style | Model card |
+|---|---|---|
+| **Junco** | clear, neutral reading voice | this page |
+| **Goldfinch** | conversational voice that laughs and breathes on cue with `[laugh]` tags | [flockspeech/goldfinch](https://huggingface.co/flockspeech/goldfinch) |
+
 | | |
 |---|---|
 | **Developed by** | Flock Speech |
@@ -168,6 +191,35 @@ predicts the STFT magnitude and phase, and the inverse STFT runs in numpy.
 **Environmental impact.** The final training run used about 3 GPU-hours on one NVIDIA T4 (70 W TDP), or about
 0.2 kWh. Architecture experiments before it used more.
 
+## FAQ
+
+**Does Junco need a GPU or an internet connection?**
+No. It runs on an ordinary CPU with ONNX Runtime. Once installed, speech is generated fully offline and your text
+never leaves the machine.
+
+**How big is it?**
+44.2 MB in total: a 17.1 MB acoustic model plus the 27.1 MB Vocos vocoder. Junco and Goldfinch share the vocoder, so
+both voices together take 61.3 MB.
+
+**Can it run on a Raspberry Pi or other ARM boards?**
+It runs on 64-bit ARM Linux wherever `onnxruntime` and `espeakng-loader` publish wheels, including 64-bit Raspberry
+Pi OS.
+
+**Can I stream audio for low latency?**
+Yes. `tts.stream(text)` yields audio sentence by sentence, so playback can start before the whole text is done.
+
+**Can I use it without Python?**
+The ONNX files run in any ONNX Runtime binding. The text front end (espeak-ng phonemes) and the small loop around the
+three models live in the [`flockspeech`](https://github.com/flockspeech/flockspeech) package, which you can port.
+
+**Does it support voice cloning or other languages?**
+No. Junco is one English (US) voice. For a casual, conversational voice, use
+[Goldfinch](https://huggingface.co/flockspeech/goldfinch).
+
+**Can I use it commercially?**
+Yes. The weights are Apache-2.0 and the vocoder is MIT. The phonemiser (espeak-ng, phonemizer) is GPL-3.0 and is
+installed separately; see the License section below.
+
 ## License
 
 - **Junco weights and configuration:** [Apache License 2.0](LICENSE). Commercial use, modification and redistribution
@@ -192,6 +244,12 @@ that suits you. See [NOTICE](NOTICE).
 }
 ```
 
+## Links
+
+- Python package: [pypi.org/project/flockspeech](https://pypi.org/project/flockspeech/)
+- Source code: [github.com/flockspeech/flockspeech](https://github.com/flockspeech/flockspeech)
+- Conversational voice: [flockspeech/goldfinch](https://huggingface.co/flockspeech/goldfinch)
+
 ## Acknowledgements
 
 Junco builds on ideas from Matcha-TTS (conditional flow matching for TTS), Glow-TTS (Monotonic Alignment Search),