docs: Add Kani-TTS-2 evaluation and RTX 5090 compatibility analysis

## Kani-TTS-2 Research
- Evaluated Kani-TTS-2 as potential TTS upgrade (3-4x faster, RTF 0.2)
- Documented benefits: zero-shot voice cloning, Apache 2.0 license, 3GB VRAM
- Identified Windows compatibility issues (pynini compilation failures)
- Created test script for future evaluation when Windows support improves

## RTX 5090 Critical Finding
- Discovered RTX 5090 (Blackwell sm_120) not supported by PyTorch
- Tested stable (2.6.0) and nightly (2.7.0.dev) - both lack sm_120 support
- Documented impact: GPU acceleration unavailable for STT/TTS
- Performance degradation: 3.5s target → 10-15s actual (CPU-only)

## Files Added
- KANI_TTS_EVALUATION.md - Comprehensive Kani-TTS-2 analysis
- RTX_5090_BLOCKER.md - GPU compatibility report with solutions
- test_kani_tts.py - Benchmark script for future testing
- fix_pytorch_cuda.bat - GPU setup script (for when support lands)

## Recommendations
- Wait 1-3 months for PyTorch sm_120 support
- Monitor PyTorch releases weekly
- Alternative: Cloud GPU (RTX 4090) or different local GPU
- Current: CPU-only mode functional but slow

## Next Steps
- Monitor: https://github.com/pytorch/pytorch/releases
- Test when available: pip install --pre torch --index-url https://download.pytorch.org/whl/nightly/cu124
- Re-evaluate Kani-TTS-2 after GPU support

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

fix_pytorch_cuda.bat

@@ -0,0 +1,43 @@
+@echo off
+echo ======================================================================
+echo Fixing PyTorch CUDA Installation
+echo ======================================================================
+echo.
+echo Current Status:
+call venv\Scripts\activate.bat
+python -c "import torch; print(f'  PyTorch: {torch.__version__}'); print(f'  CUDA: {torch.cuda.is_available()}')"
+echo.
+
+echo ======================================================================
+echo This will:
+echo   1. Uninstall CPU-only PyTorch
+echo   2. Install CUDA 12.1-enabled PyTorch
+echo   3. Verify RTX 5090 is accessible
+echo ======================================================================
+echo.
+
+set /p continue="Continue? (y/n): "
+if /i not "%continue%"=="y" (
+    echo Cancelled.
+    exit /b 1
+)
+
+echo.
+echo [1/3] Uninstalling CPU PyTorch...
+pip uninstall torch torchaudio torchvision -y
+
+echo.
+echo [2/3] Installing CUDA PyTorch (this may take a few minutes)...
+pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
+
+echo.
+echo [3/3] Verifying installation...
+python -c "import torch; print(f'\nPyTorch: {torch.__version__}'); print(f'CUDA Available: {torch.cuda.is_available()}'); print(f'GPU: {torch.cuda.get_device_name(0) if torch.cuda.is_available() else \"N/A\"}'); print(f'CUDA Version: {torch.version.cuda if torch.cuda.is_available() else \"N/A\"}')"
+
+echo.
+echo ======================================================================
+echo Done! Your TTS and STT should now use GPU acceleration.
+echo ======================================================================
+echo.
+echo Next: Run the bot and check performance improvement!
+pause