Hitonabi
09a1c98514
- 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>
41 lines
2.1 KiB
Python
41 lines
2.1 KiB
Python
# -*- coding: utf-8 -*-
|
|
"""Stabilität gegen Stimm-Kollaps: temp 0.9 mit/ohne noise_clamp. F0-Verteilung + Whisper + RTF.
|
|
Mehr Samples, um einen Kollaps (tiefe F0) zu provozieren und zu sehen, ob noise_clamp ihn dämpft."""
|
|
import os, time, numpy as np, librosa, soundfile as sf
|
|
from pocket_tts import TTSModel
|
|
from faster_whisper import WhisperModel
|
|
|
|
BASE = r"F:\Coding Stuff\mission-control-2\client\lucy-tts"
|
|
src,_ = librosa.load(os.path.join(BASE,"ref.mp3"), sr=24000, mono=True)
|
|
srt,_ = librosa.effects.trim(src, top_db=30); ref=os.path.join(BASE,"ref.wav")
|
|
sf.write(ref, srt[:int(18*24000)], 24000)
|
|
LEAD="Tja. "
|
|
TEXTS = ["Hallo Commander, ich höre dich.","Natürlich, das mache ich sofort für dich.",
|
|
"Die Hitze ist heute wirklich heftig.","Klar, ich kümmere mich gleich darum.",
|
|
"Guten Morgen, Commander, alles sauber.","Kein Problem, ich erledige das jetzt.",
|
|
"Das Backup lief ohne Fehler durch.","Verstanden, Commander, ich bleibe dran."]
|
|
w = WhisperModel("small", device="cpu", compute_type="int8")
|
|
|
|
def f0_of(a, sr):
|
|
f0,_,_ = librosa.pyin(a, fmin=80, fmax=400, sr=sr, frame_length=1024)
|
|
v=f0[~np.isnan(f0)]; return float(np.median(v)) if v.size else float("nan")
|
|
|
|
def run(temp, nc):
|
|
m = TTSModel.load_model(language="german_24l", lsd_decode_steps=6, temp=temp, noise_clamp=nc)
|
|
vs = m.get_state_for_audio_prompt(ref); sr=m.sample_rate
|
|
print(f"=== temp={temp} noise_clamp={nc} ===", flush=True)
|
|
f0s=[]; rtfs=[]
|
|
for i in range(12):
|
|
t=TEXTS[i%len(TEXTS)]
|
|
t0=time.time(); a=m.generate_audio(vs, LEAD+t, frames_after_eos=4); dt=time.time()-t0
|
|
a=a.numpy() if hasattr(a,"numpy") else np.asarray(a); a=np.asarray(a,dtype=np.float32).reshape(-1)
|
|
f0=f0_of(a,sr); f0s.append(f0); rtfs.append(dt/max(a.size/sr,0.01))
|
|
flag=" <<< MÄNNLICH/Kollaps?" if (f0==f0 and f0<150) else ""
|
|
print(f" [{i:2}] F0={f0:6.1f}Hz{flag}", flush=True)
|
|
arr=np.array([x for x in f0s if x==x])
|
|
print(f" -> F0 median {np.median(arr):.0f} min {arr.min():.0f} max {arr.max():.0f} | RTF~{np.median(rtfs):.2f}", flush=True)
|
|
|
|
run(0.9, None)
|
|
run(0.9, 3.0)
|
|
print("NC_DONE")
|