Локальная озвучка через Silero: нормализатор русского текста под TTS, рендер по главам, замечание про AVX2

SKILL.md

@@ -202,9 +202,41 @@ the external repo is still never edited.
    stays viable. Hand the result to the `prepare-audiobooks` skill for covers
    and library layout.
 
+### Prefer local Silero over edge-tts
+
+edge-tts drops fragments silently under load — measured 1 of 49 on one run and
+7 of 49 on the next, at *fewer* workers, so it is volume- not concurrency-bound.
+`scripts/silero_render.py` replaces the external synthesis stage entirely with a
+local model: no network, no dropouts, no `repair` cycle, free.
+
+```bash
+pip install torch numpy --index-url https://download.pytorch.org/whl/cpu
+curl -O https://models.silero.ai/models/tts/ru/v5_5_ru.pt      # 145 МБ
+python scripts/silero_render.py v5_5_ru.pt <workdir>/translations_tts <out> \
+  --album "Название" --author "Автор" --speaker eugene --tempo 0.87 \
+  --skip 0 1 2 3 37
+```
+
+**Check `lscpu | grep avx2` before choosing the host.** PyTorch needs AVX2;
+without it inference is ~30x slower — measured 3.4x realtime on a Celeron N5095
+(SSE4 only) versus 97x on a Ryzen 7 5800H. Use 8 threads, not 16: hyperthreading
+loses (97x vs 83x).
+
+`scripts/tts_normalize.py` prepares the text — Latin script is what makes a
+Russian voice sound worst, and a full book carries far more of it than a sample
+chapter suggests (37 unique tokens in one chapter, 728 across the book). It maps
+named entities and acronyms by hand with stress marks, transliterates the rest
+by rule, spells out numbers, and drops URLs. It also generates Russian chapter
+titles, since translated headings often stay English and the intro fragment
+would otherwise read them aloud in Latin.
+
+Voice tempo: SSML `<prosody rate>` quantizes to named levels, so percentages
+cluster instead of stepping evenly. For fine control use `--tempo`, which
+time-stretches with ffmpeg and preserves pitch.
+
 The phonetics stage (`07_extract_terms.py` + `08_generate_phonetics.py`) is
-worth running first for a technical book, or the Russian voice will mangle
-every English term.
+worth running first for a technical book **when using edge-tts**; with
+`tts_normalize.py` it is redundant.
 
 **Ordering constraint for the whole stage:** `verify` and `split` both read
 `audiobook/temp_audio/`, and the external script's `cleanup_temp_files()`