Lucy-TTS/F5: Skripte + Batches versionieren, schwere Assets ignoriert

- pocket_server.py (Produktions-TTS mit Stimmen-Waechter), text_norm, Bench-/Diag-Skripte
- lucy-f5: f5_server/f5_test/bench_dml (DirectML-Experiment, Phase C/D offen)
- .gitignore: venvs/Modelle/Audio/Logs der beiden Ordner + box_recon/gemma_swap-Scratch

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

client/lucy-tts/tune_natural.py

@@ -0,0 +1,61 @@
+# -*- coding: utf-8 -*-
+"""Naturalness-Sweep gegen 'Roboter/abgehackt': temperature, lsd hoch, + 2 Referenz-Fenster.
+Wörter sind laut Whisper alle da -> Problem ist Prosodie/Timbre, nicht Content."""
+import os, time, numpy as np, soundfile as sf, librosa
+from pocket_tts import TTSModel
+
+BASE = r"F:\Coding Stuff\mission-control-2\client\lucy-tts"
+OUT = r"C:\Users\TobisPC\Desktop\lucy_natural"; os.makedirs(OUT, exist_ok=True)
+
+# Zwei Referenz-Fenster aus der EL-Saber-MP3
+src, _ = librosa.load(os.path.join(BASE, "ref.mp3"), sr=24000, mono=True)
+srt, _ = librosa.effects.trim(src, top_db=30)
+ref18 = os.path.join(BASE, "ref.wav")          # aktuell: erste 18s
+sf.write(ref18, srt[:int(18*24000)], 24000)
+refC = os.path.join(BASE, "ref_C.wav")          # XTTS-Liebling: Sek 18..27 (9s)
+segC = src[int(18*24000):int(27*24000)]
+segCt, _ = librosa.effects.trim(segC, top_db=30)
+sf.write(refC, segCt, 24000)
+
+SENT = {
+ "kurz":  "Hallo Commander, ich höre dich.",
+ "mittel":"Guten Morgen, Commander. Das Backup ist sauber durchgelaufen und es gab keine Fehler.",
+}
+
+def cleanup_v2(a, sr):
+    a = np.asarray(a, dtype=np.float32).reshape(-1)
+    if a.size == 0: return a
+    peak = float(np.max(np.abs(a)))
+    if peak > 0: a = a * (0.95 / peak)
+    yt, _ = librosa.effects.trim(a, top_db=45); a = yt if yt.size else a
+    fi = min(int(0.01*sr), a.size//2)
+    if fi > 0:
+        a[:fi] *= np.linspace(0.,1.,fi,dtype=np.float32)
+        a[-fi:] *= np.linspace(1.,0.,fi,dtype=np.float32)
+    pad = np.zeros(int(0.09*sr), dtype=np.float32)
+    return np.concatenate([pad, a, pad])
+
+# (tag, lsd, temp, ref)
+COMBOS = [
+ ("A_lsd6_t070_ref18", 6, 0.70, ref18),
+ ("B_lsd6_t090_ref18", 6, 0.90, ref18),
+ ("C_lsd6_t105_ref18", 6, 1.05, ref18),
+ ("D_lsd8_t090_ref18", 8, 0.90, ref18),
+ ("E_lsd12_t090_ref18",12, 0.90, ref18),
+ ("F_lsd6_t090_refC",  6, 0.90, refC),
+]
+
+for tag, lsd, temp, ref in COMBOS:
+    t0 = time.time()
+    m = TTSModel.load_model(language="german_24l", lsd_decode_steps=lsd, temp=temp)
+    vs = m.get_state_for_audio_prompt(ref)
+    sr = m.sample_rate
+    print(f"== {tag} (load {time.time()-t0:.1f}s) ==", flush=True)
+    for name, text in SENT.items():
+        t0 = time.time()
+        audio = m.generate_audio(vs, text, frames_after_eos=4); dt = time.time()-t0
+        a = audio.numpy() if hasattr(audio,"numpy") else np.asarray(audio)
+        a = cleanup_v2(a, sr); secs = a.size/sr
+        sf.write(os.path.join(OUT, f"{tag}_{name}.wav"), a, sr)
+        print(f"   [{name:6}] gen={dt:5.2f}s audio={secs:5.2f}s RTF={dt/max(secs,0.01):.2f}", flush=True)
+print("NATURAL_DONE", flush=True)