58 أسطر
2.2 KiB
Markdown
58 أسطر
2.2 KiB
Markdown
# Q2 — Fine-tuning an Arabic TTS or STT
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⏱ **Budget: ~15 minutes** · Weight: 25%
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## Choose ONE option
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- **Option A — TTS.** Fine-tune an open Arabic (or multilingual) text-to-speech model — e.g. Coqui **XTTS-v2**, **VITS**, or **StyleTTS2** — on a single-speaker Arabic dataset.
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- **Option B — STT.** Fine-tune **Whisper** (e.g. `whisper-small`, `large-v3`) on Arabic speech — e.g. Mozilla **Common Voice `ar`**, **MGB-2**, or a custom corpus.
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## Produce a runnable guide covering
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1. **Model & dataset choice** — justify it; cite dataset sizes, license, and dialect (MSA vs. Egyptian vs. Gulf vs. Maghrebi).
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2. **Data preprocessing** — audio resampling/normalization, text normalization, and the Arabic-specific gotchas: **diacritization (تشكيل)**, letter variants (أ/إ/آ, ة/ه, ى/ي), and (for STT) whether to strip diacritics before computing WER. Train/val split.
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3. **Training setup** — framework (e.g. Hugging Face Trainer, Coqui TTS, NeMo), **LoRA vs. full fine-tune**, key hyperparameters (batch size, LR, epochs, warmup), hardware, and a rough time/cost estimate.
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4. **Evaluation** — for STT: **WER/CER** (and how to compute them fairly for Arabic); for TTS: **MOS**, **speaker similarity (SECS)**, and using an ASR to measure intelligibility. Include the actual metric definitions/commands.
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5. **Deployment on Ghaymah** — GPU sizing, container vs. function, serving stack, latency, and how the model is served behind an API.
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6. **Risks & mitigations** — dialect coverage, hallucination, diacritic fidelity, MSA vs. dialect mismatch, data licensing.
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Include **real code snippets** (Python / Hugging Face / CLI). Cite sources inline.
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## Deliverable
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Fill in the template below. State clearly which option you chose.
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---
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## ANSWER — Arabic TTS/STT Fine-tune
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**Option chosen:** A / B (delete one)
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### 1. Model & dataset choice
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> _write here_
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### 2. Data preprocessing
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> _write here + code snippets_
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### 3. Training setup
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> _write here + code/config snippets_
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### 4. Evaluation
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> _write here + metric definitions/commands_
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### 5. Deployment on Ghaymah
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> _write here_
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### 6. Risks & mitigations
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| Risk | Mitigation |
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|---|---|
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