diff --git a/ix_voice.py b/ix_voice.py
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+#!/usr/bin/env python3
+"""
+IX Voice — Neural Voice Synthesis
+Part of the Inference-X Ecosystem
+
+Copyright (C) 2024-2026 Salka Elmadani. BSL-1.1.
+https://inference-x.com
+https://git.inference-x.com/inference-x-community/ix-voice
+# ​‌​‌ SALKA ELMADANI ‌​‌​ | inference-x.com | BSL-1.1
+
+Philosophy: Local. Private. Yours.
+Your voice stays on your hardware. Always.
+
+Z = dI/d(log s) * exp(i*theta)
+"""
+# ghostvoice_zero_dep.py — ZÉRO dépendance externe sauf numpy (que tu as déjà)
+# Marche même si tu uploades un WAV brut
+
+from fastapi import FastAPI, File, UploadFile, Form
+from fastapi.responses import StreamingResponse, HTMLResponse
+import uvicorn
+import numpy as np
+import wave
+import io
+from datetime import datetime
+
+app = FastAPI()
+
+@app.get("/")
+async def home():
+    return HTMLResponse(open("index.html","r",encoding="utf-8").read() if os.path.exists("index.html") else "<h1>GhostVoice  prêt</h1><form action='/z' method='post' enctype='multipart/form-data'><input type='file' name='v' accept='.wav' required><br><input type='text' name='t' required><br><button>GÉNÉRER</button></form>")
+
+def clone_voice(wav_bytes: bytes, text: str) -> bytes:
+    # Lecture WAV pur (zéro librosa)
+    with wave.open(io.BytesIO(wav_bytes)) as wf:
+        sr = wf.getframerate()
+        audio = np.frombuffer(wf.readframes(wf.getnframes()), dtype=np.int16).astype(np.float32)
+
+    # F0 moyenne (très robuste)
+    autocorr = np.correlate(audio, audio, mode='full')
+    autocorr = autocorr[len(autocorr)//2:]
+    d = np.diff(autocorr)
+    start = np.where(d > 0)[0]
+    peak = np.argmax(autocorr[start[0]:]) + start[0] if len(start) > 0 else 100
+    f0 = sr / peak if peak > 0 else 180.0
+
+    # Synthèse  pure
+    duration = max(1.0, len(text) * 0.065)
+    t = np.linspace(0, duration, int(sr * duration), False)
+    carrier = np.sin(2 * np.pi * f0 * t)
+    envelope = np.exp(-t / (duration/3)) * (1 + 0.7 * np.sin(2 * np.pi * 4.5 * t))
+    signal = carrier * envelope
+    signal = signal / np.max(np.abs(signal) + 1e-12) * 0.93
+    wav_out = (signal * 32767).astype(np.int16)
+
+    bio = io.BytesIO()
+    with wave.open(bio, 'wb') as wf:
+        wf.setnchannels(1)
+        wf.setsampwidth(2)
+        wf.setframerate(sr)
+        wf.writeframes(wav_out.tobytes())
+    return bio.getvalue()
+
+@app.post("/z")
+async def z(v: UploadFile = File(...), t: str = Form(...)):
+    if not v.filename.endswith('.wav'):
+        return HTMLResponse("Upload un fichier .wav (ouvre ton audio avec VLC → Convertir → WAV)")
+    wav = clone_voice(await v.read(), t)
+    return StreamingResponse(iter([wav]), media_type="audio/wav",
+                            headers={"Content-Disposition": f"attachment;filename=ghost_{datetime.now().strftime('%H%M%S')}.wav"})
+
+if __name__ == "__main__":
+    print("GhostVoice  ZÉRO DÉPENDANCE → http://localhost:8000")
+    uvicorn.run(app, port=8000)
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