fix(s2s): validate OpenWakeWord detection threshold

src/rai_s2s/rai_s2s/asr/models/open_wake_word.py

@@ -59,14 +59,18 @@ def __init__(self, wake_word_model_path: str, threshold: float = 0.1):
         """
         super(OpenWakeWord, self).__init__()
         self.model_name = "open_wake_word"
+        if not isinstance(threshold, (int, float)) or isinstance(threshold, bool):
+            raise ValueError("threshold must be a number in (0, 1]")
+        if not (0.0 < float(threshold) <= 1.0) or threshold != threshold:
+            raise ValueError("threshold must be in (0, 1]")
+        self.threshold = float(threshold)
         download_models()
         self.model = OWWModel(
             wakeword_models=[
                 wake_word_model_path,
             ],
             inference_framework="onnx",
         )
-        self.threshold = threshold
 
     def detect(
         self, audio_data: NDArray, input_parameters: dict[str, Any]

tests/test_open_wake_word_threshold.py

@@ -0,0 +1,34 @@
+# Copyright (C) 2026 Robotec.AI
+import pytest
+
+from rai_s2s.asr.models.open_wake_word import OpenWakeWord
+
+
+def test_open_wake_word_rejects_invalid_threshold(monkeypatch):
+    monkeypatch.setattr(
+        "rai_s2s.asr.models.open_wake_word.download_models", lambda: None
+    )
+
+    class _Boom:
+        def __init__(self, *a, **k):
+            raise AssertionError("OWWModel should not load on bad threshold")
+
+    monkeypatch.setattr("rai_s2s.asr.models.open_wake_word.OWWModel", _Boom)
+
+    for bad in (0, -0.1, 1.1, float("nan"), True):
+        with pytest.raises(ValueError, match="threshold"):
+            OpenWakeWord(wake_word_model_path="unused.onnx", threshold=bad)
+
+
+def test_open_wake_word_accepts_valid_threshold(monkeypatch):
+    monkeypatch.setattr(
+        "rai_s2s.asr.models.open_wake_word.download_models", lambda: None
+    )
+
+    class _Ok:
+        def __init__(self, *a, **k):
+            pass
+
+    monkeypatch.setattr("rai_s2s.asr.models.open_wake_word.OWWModel", _Ok)
+    m = OpenWakeWord(wake_word_model_path="unused.onnx", threshold=0.5)
+    assert m.threshold == 0.5