Add XTTS-v2 as first TTS backend, extensible for more

Mirrors the ASR backend pattern exactly: a BACKENDS dict in
tts/router.py maps a backend name to its worker URL, so adding the
next backend is just a new worker file + venv + supervisord entry +
one dict line. XTTS-v2 runs in its own venv (--system-site-packages,
inherits base image torch/CUDA) as a new supervisord program on
port 8005.

XTTS is zero-shot voice cloning, so a reference-voice library was
added (/tts/voices CRUD, stored under /srv/tts/voices) — synthesis
requires picking a previously uploaded voice. Results and model
cache live under /srv/tts/{results,models-cache}, new quadlet
volumes, owned by the same 983:983 user as the existing /srv/asr
dirs.

Fixed two environment issues uncovered while getting XTTS to
actually run inside the container (non-root user, root-built venvs):
- coqui-tts only pins transformers>=4.57 with no ceiling, so pip
  installed an incompatible 5.x; pinned to the last 4.x release.
- HOME defaults to /app (owned by root) for the container's runtime
  user, so numba/matplotlib/torch cache writes failed; HOME is now
  forced to /tmp in all three workers (faster_whisper, qwen3, xtts)
  before any of those libraries get imported.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

app/asr/workers/qwen3_worker.py

@@ -14,6 +14,12 @@ import sys
 sys.path.insert(0, "/app")
 from asr.config import DEVICE, MODEL_CACHE, ensure_runtime_dirs
 
+import os
+# 컨테이너는 983 유저로 실행되는데 HOME(/app)이 root 소유라 numba/matplotlib/torch가
+# 각자 ~/.cache, ~/.config 아래에 쓰려다 실패한다. HOME을 쓰기 가능한 곳으로 돌린다.
+os.environ["HOME"] = "/tmp"  # 컨테이너 기본 HOME=/app은 983 유저가 쓰기 불가 (setdefault로는 덮어쓰기 안 됨)
+os.environ.setdefault("NUMBA_CACHE_DIR", "/tmp/numba_cache")
+
 app = FastAPI(title="ASR Qwen3 Worker")
 
 _PIPE_CACHE: Dict[str, Any] = {}