修回声: 房间 IR 含 30ms 传播延迟(声源到麦克风 10.3m 的声程)且前两次反射与直达声同量级(30ms 处 0dB/40ms 处 -1.6dB), 与零延迟的干声相加 -> 湿声晚 30ms 还很响 = 回声; 处理 IR(裁前 22ms 静音 + 前 55ms 余弦渐入, 直达声段 0 -> -23.6dB)再把 gain 重标 0.126->0.4 补回混响量; 脉冲取证: 修前 120ms 处 -26dBFS 孤立峰(+12dB), 修后包络单调衰减无孤立峰; 新增 测试/test_echo.py 与 工具/重做混响IR.py, 原 IR 备份 .orig.wav

测试/test_echo.py

@@ -0,0 +1,92 @@
+"""回声诊断: 播单脉冲, 录数字输出, 看是平滑混响衰减还是离散回声。
+
+离散回声 = 主峰之后出现孤立的、比周围明显高的峰(延迟 20ms 以上);
+平滑混响 = 包络单调下降。分湿量 0 / 0.3 各测一次, 好判断回声是不是混响造成的。
+"""
+from __future__ import annotations
+
+import json
+import subprocess
+import time
+import urllib.request
+from pathlib import Path
+
+import numpy as np
+from scipy.io import wavfile
+
+RATE = 96000
+MAT = Path("/tmp/echo_mat.wav")
+REC = Path("/tmp/echo_rec.wav")
+API = "http://127.0.0.1:8789"
+
+
+def api(path: str, payload: dict[str, object] | None = None) -> dict[str, object]:
+    """调面板 API。"""
+    headers = {"Content-Type": "application/json"}
+    data = json.dumps(payload).encode() if payload else None
+    req = urllib.request.Request(API + path, data=data, headers=headers)
+    with urllib.request.urlopen(req, timeout=5) as r:
+        return json.loads(r.read())
+
+
+def db(x: float) -> float:
+    """线性转 dBFS。"""
+    return 20 * np.log10(max(float(x), 1e-7))
+
+
+def find_monitor() -> str:
+    """找数字输出的 monitor 名字。"""
+    out = subprocess.run(["pw-dump"], capture_output=True, text=True, timeout=20).stdout
+    for line in out.splitlines():
+        if '"node.name"' in line and "iec958" in line:
+            return line.split('"')[3] + ".monitor"
+    return ""
+
+
+def main() -> None:
+    """跑诊断。"""
+    n = int(RATE * 3.5)
+    x = np.zeros(n, dtype=np.float32)
+    x[int(RATE * 1.0)] = 0.5
+    wavfile.write(MAT, RATE, (x * 32767).astype(np.int16))
+
+    mon = find_monitor()
+    print("录音设备:", mon or "(没找到, 用默认)")
+    args = ["pw-record", "--rate", str(RATE), "--channels", "2", "--format", "s16", str(REC)]
+    if mon:
+        args[1:1] = ["--target", mon]
+
+    # 静音 Chrome(它会往默认输出送声音, 污染测量), 完事恢复
+    subprocess.run(["wpctl", "set-mute", "90", "1"], capture_output=True, timeout=10)
+
+    for wet in (0.0, 0.3):
+        api("/api/wet", {"wet": wet})
+        time.sleep(0.3)
+        REC.unlink(missing_ok=True)
+        rec = subprocess.Popen(args)
+        time.sleep(0.6)
+        subprocess.run(["pw-play", "--target", "collaplex_vsink", str(MAT)], timeout=30)
+        time.sleep(0.8)
+        rec.terminate()
+        rec.wait(timeout=5)
+
+        _r, data = wavfile.read(REC)
+        mono = data[:, 0].astype(np.float64) / 32768.0
+        pk = int(np.argmax(np.abs(mono)))
+        print(f"\n湿量 {wet:.2f}: 主峰 @ {pk / RATE * 1000:.1f} ms, {db(abs(mono[pk])):.1f} dBFS")
+        seg: list[float] = []
+        for k in range(1, 61):
+            a = pk + int(RATE * 0.02 * (k - 1))
+            b = pk + int(RATE * 0.02 * k)
+            if b > len(mono):
+                break
+            seg.append(db(np.max(np.abs(mono[a:b]))))
+        print("  主峰后每 20ms 包络(dBFS):")
+        print("   ", " ".join(f"{v:.0f}" for v in seg[:40]))
+
+    api("/api/wet", {"wet": 0.3})
+    subprocess.run(["wpctl", "set-mute", "90", "0"], capture_output=True, timeout=10)
+    print("\n(湿量恢复 0.3, Chrome 已取消静音)")
+
+
+main()