docs(data): integrate Common Voice Pashto dataset and contribution guide

CONTRIBUTING.md

@@ -8,6 +8,21 @@ Thanks for helping build open Pashto AI resources.
 - Model training/evaluation scripts
 - Documentation, issue triage, and testing
 
+## 🌐 Mozilla Common Voice Path
+You can contribute to Pashto data directly on Common Voice and connect it back
+to this project.
+
+Common Voice Pashto actions:
+- Speak: `https://commonvoice.mozilla.org/ps/speak`
+- Write: `https://commonvoice.mozilla.org/ps/write`
+- Listen: `https://commonvoice.mozilla.org/ps/listen`
+- Review: `https://commonvoice.mozilla.org/ps/review`
+
+Then contribute here by opening an issue/PR with:
+- what you worked on,
+- what data quality gap you observed,
+- what concrete follow-up is needed in this repository.
+
 ## 🔄 Contribution flow
 1. Open or pick an issue.
 2. Comment your plan.

README.md

@@ -22,6 +22,18 @@ Community-led open-source project to make Pashto a first-class language in AI sp
 - Keep work reproducible, transparent, and contribution-friendly.
 - Focus on public good and broad accessibility.
 
+## 📚 Featured External Dataset
+- `Common Voice Scripted Speech 24.0 - Pashto`
+- Source:
+  `https://datacollective.mozillafoundation.org/datasets/cmj8u3pnb00llnxxbfvxo3b14`
+- Project integration guide: `docs/common_voice_pashto_24.md`
+
+## 🙌 Contribute Through Mozilla Common Voice
+- Speak: `https://commonvoice.mozilla.org/ps/speak`
+- Write: `https://commonvoice.mozilla.org/ps/write`
+- Listen: `https://commonvoice.mozilla.org/ps/listen`
+- Review: `https://commonvoice.mozilla.org/ps/review`
+
 ## 🚀 Start Here
 - 📘 Purpose: `PROJECT_PURPOSE.md`
 - 🤝 Contributing: `CONTRIBUTING.md`

data/README.md

@@ -9,6 +9,17 @@
 - `../docs/pashto_normalization_v0.1.md` baseline normalization policy
 - `../scripts/validate_normalization.py` basic file validator
 
+## External Source: Mozilla Common Voice (Pashto)
+- Dataset: `Common Voice Scripted Speech 24.0 - Pashto`
+- Source page:
+  `https://datacollective.mozillafoundation.org/datasets/cmj8u3pnb00llnxxbfvxo3b14`
+- Local target path: `data/raw/common_voice_scripted_ps_v24/`
+- Integration guide: `../docs/common_voice_pashto_24.md`
+
+### Notes
+- Keep raw downloaded dataset files out of git.
+- Track source URL + version in experiment notes for reproducibility.
+
 ## Validate Seed File
 ```bash
 python scripts/validate_normalization.py data/processed/normalization_seed_v0.1.tsv

docs/common_voice_pashto_24.md

@@ -0,0 +1,52 @@
+# Common Voice Scripted Speech 24.0 - Pashto Integration Guide
+
+This project recognizes Mozilla Common Voice as a major source for Pashto ASR
+progress and community participation.
+
+## Dataset
+- Name: `Common Voice Scripted Speech 24.0 - Pashto`
+- Dataset page:
+  `https://datacollective.mozillafoundation.org/datasets/cmj8u3pnb00llnxxbfvxo3b14`
+- Release date: `2025-12-05`
+- Format: `MP3` with TSV metadata
+- Approximate size: `49.98 GB`
+- License: `CC0-1.0`
+
+## Important Usage Rules
+- Do not attempt to identify speakers.
+- Do not re-host or re-share the raw dataset files.
+- Keep provenance and version information when reporting experiments.
+
+## How To Use In This Repository
+1. Download from the official Mozilla Data Collective page.
+2. Extract locally under:
+   `data/raw/common_voice_scripted_ps_v24/`
+3. Keep raw audio out of git.
+4. Use project scripts/docs for normalization, splits, and benchmarking.
+
+Recommended local structure:
+```text
+data/raw/common_voice_scripted_ps_v24/
+  clips/
+  train.tsv
+  dev.tsv
+  test.tsv
+```
+
+## How To Contribute Through Mozilla Common Voice
+Contributors can directly improve Pashto resources on Common Voice:
+- Speak: `https://commonvoice.mozilla.org/ps/speak`
+- Write: `https://commonvoice.mozilla.org/ps/write`
+- Listen: `https://commonvoice.mozilla.org/ps/listen`
+- Review: `https://commonvoice.mozilla.org/ps/review`
+
+## Contribution Loop Back To This Project
+After contributing on Common Voice, open an issue/PR here and share:
+- what task you worked on (speak/write/listen/review),
+- what quality gaps you observed,
+- what dataset or modeling step should be improved next.
+
+Use issue labels:
+- `data`
+- `good first issue`
+- `help wanted`