Add NVIDIA NeMo Text Processing example

examples/nemo-text-processing/.gitignore

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+startup.log
+__pycache__/
+*.pyc
+.ipynb_checkpoints/

examples/nemo-text-processing/.saturn/saturn.json

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+{
+  "name": "example-nemo-text-processing",
+  "image_uri": "public.ecr.aws/saturncloud/saturn-python:2025.05.01",
+  "description": "NVIDIA NeMo Text Processing — normalize text for TTS and ASR pipelines. Demonstrates Text Normalization (written→spoken) and Inverse Text Normalization (spoken→written) across 15 languages.",
+  "working_directory": "/home/jovyan/examples/examples/nemo-text-processing",
+  "start_script": "bash start.sh",
+  "git_repositories": [
+    {
+      "url": "https://github.com/saturncloud/examples",
+      "path": "/home/jovyan/examples"
+    }
+  ],
+  "jupyter_server": {
+    "disk_space": "10Gi",
+    "instance_type": "large",
+    "auto_shutoff": "1 hour"
+  },
+  "version": "2022.01.06"
+}

examples/nemo-text-processing/README.md

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+# 📝 NVIDIA NeMo Text Processing
+
+### **Overview**
+
+This template demonstrates [NVIDIA NeMo Text Processing](https://github.com/NVIDIA/NeMo-text-processing) — a library for normalizing text in speech AI pipelines. It covers both directions of text conversion used in production ASR and TTS systems.
+
+* **Hardware:** CPU Large (2 cores, 16 GB RAM) — no GPU required
+* **Python:** 3.10+
+* **Use Case:** Speech AI preprocessing — TTS pipelines, ASR post-processing, multilingual text normalization
+
+---
+
+### **What it does**
+
+| Operation | Direction | Example |
+|-----------|-----------|---------|
+| **Text Normalization (TN)** | Written → Spoken | `"$4.99"` → `"four dollars and ninety nine cents"` |
+| **Inverse Text Normalization (ITN)** | Spoken → Written | `"three thirty p m"` → `"3:30 p.m."` |
+
+Both operations are powered by **Weighted Finite-State Transducers (WFST)** — fast, rule-based grammars that require no model download and no GPU.
+
+---
+
+### **Tech Stack**
+
+* **NeMo Text Processing (`nemo_text_processing`):** Core normalization library from NVIDIA.
+* **Pynini / OpenFst:** WFST engine that powers the grammar rules.
+* **15 languages supported:** English, German, Spanish, French, Hungarian, Swedish, Mandarin, Arabic, Italian, Armenian, Japanese, Hindi, Korean, Vietnamese, Portuguese.
+
+---
+
+## 🪐 Using on Saturn Cloud
+
+### 1. Create the workspace from the template
+
+In Saturn Cloud, go to **New Resource → Workspace → Templates** and select **NeMo Text Processing**.
+
+### 2. Start the workspace
+
+Click **Start**. The startup script installs `nemo_text_processing` automatically. This takes 3–5 minutes on first start — watch progress in the **Logs** panel.
+
+### 3. Open the notebook
+
+Once the workspace shows **Running**, click **JupyterLab**. Open `nemo_text_processing_demo.ipynb` from the file browser and run the cells top to bottom.
+
+---
+
+## 🛠️ Local Setup
+
+```bash
+pip install nemo_text_processing
+```
+
+Then open `nemo_text_processing_demo.ipynb` in JupyterLab.
+
+> **Note:** pip install requires Linux x86_64. On macOS or Windows use conda:
+> ```bash
+> conda create --name nemo_tn python=3.10
+> conda activate nemo_tn
+> conda install -c conda-forge pynini
+> pip install nemo_text_processing
+> ```
+
+---
+
+## 📓 Notebook contents
+
+The demo notebook covers six sections:
+
+1. **Verify Installation** — confirms the library is ready
+2. **Text Normalization** — numbers, dates, times, abbreviations, measurements in English
+3. **Multilingual TN** — same operations in German and Spanish
+4. **Inverse Text Normalization** — convert ASR output back to written form
+5. **Batch Processing** — normalize a list of texts in parallel
+6. **TTS / ASR Pipeline Examples** — end-to-end pre/post-processing scenarios
+7. **Try It Yourself** — sandbox cells to test your own text
+
+---
+
+## ⚙️ Changing the language
+
+Pass any supported language code to the `Normalizer` or `InverseNormalizer`:
+
+```python
+normalizer = Normalizer(input_case='cased', lang='de')   # German
+normalizer = Normalizer(input_case='cased', lang='es')   # Spanish
+normalizer = Normalizer(input_case='cased', lang='zh')   # Mandarin
+```
+
+Supported codes: `en` `de` `es` `fr` `hu` `sv` `zh` `ar` `it` `hy` `ja` `hi` `ko` `vi` `pt`
+
+---
+
+## 🔗 Resources
+
+* **NeMo Text Processing repo:** [github.com/NVIDIA/NeMo-text-processing](https://github.com/NVIDIA/NeMo-text-processing)
+* **Official tutorials:** [github.com/NVIDIA/NeMo-text-processing/tree/main/tutorials](https://github.com/NVIDIA/NeMo-text-processing/tree/main/tutorials)
+* **Saturn Cloud:** [saturncloud.io](https://saturncloud.io/)