diff --git a/tinyml-modelmaker/tests/test_config_validation.py b/tinyml-modelmaker/tests/test_config_validation.py
index 26bcd8a..bb8dd2e 100644
--- a/tinyml-modelmaker/tests/test_config_validation.py
+++ b/tinyml-modelmaker/tests/test_config_validation.py
@@ -10,6 +10,8 @@
 import pytest
 import yaml
 
+from tinyml_modelmaker.ai_modules.audio import training as audio_training
+from tinyml_modelmaker.ai_modules.audio import constants as audio_constants
 from tinyml_modelmaker.ai_modules.timeseries import training, constants
 
 
@@ -38,8 +40,12 @@ def _find_example_configs():
 
 EXAMPLE_CONFIGS = _find_example_configs()
 
-# Known valid task types (timeseries + vision)
-KNOWN_TASK_TYPES = set(constants.TASK_TYPE_TO_CATEGORY.keys()) | {"image_classification"}
+# Known valid task types (timeseries + vision + audio)
+KNOWN_TASK_TYPES = (
+    set(constants.TASK_TYPE_TO_CATEGORY.keys())
+    | set(audio_constants.TASK_TYPES)
+    | {"image_classification"}
+)
 
 # Required top-level keys in every config
 REQUIRED_SECTIONS = {"common", "training"}
@@ -150,7 +156,8 @@ def test_model_name_exists_in_registry(self, config_path):
         if task_type == "image_classification":
             pytest.skip("Vision model registry not tested here")
 
-        desc = training.get_model_description(model_name)
+        registry = audio_training if task_type in audio_constants.TASK_TYPES else training
+        desc = registry.get_model_description(model_name)
         assert desc is not None, (
             f"Config references model '{model_name}' which is not in the registry"
         )
diff --git a/tinyml-modelmaker/tests/test_constants.py b/tinyml-modelmaker/tests/test_constants.py
index 856e8d6..99e0d6b 100644
--- a/tinyml-modelmaker/tests/test_constants.py
+++ b/tinyml-modelmaker/tests/test_constants.py
@@ -92,8 +92,9 @@ def test_anomaly_returns_classes(self):
             == ts_constants.DATA_DIR_CLASSES
         )
 
-    def test_unknown_category_returns_classes(self):
-        assert ts_constants.get_default_data_dir_for_task("something_else") == ts_constants.DATA_DIR_CLASSES
+    def test_unknown_category_raises(self):
+        with pytest.raises(ValueError, match="Unsupported task_category"):
+            ts_constants.get_default_data_dir_for_task("something_else")
 
     def test_vision_returns_classes(self):
         # Vision module always returns 'classes'
diff --git a/tinyml-modelmaker/tests/test_cross_device.py b/tinyml-modelmaker/tests/test_cross_device.py
index 4f4c1d8..73eceea 100644
--- a/tinyml-modelmaker/tests/test_cross_device.py
+++ b/tinyml-modelmaker/tests/test_cross_device.py
@@ -355,7 +355,7 @@ class TestQuantizationFlags:
     def test_float_mode_no_normalize(self, task_category):
         """Quantization=0 (float) should set skip_normalize=False, output_int=False."""
         skip, output = constants.get_skip_normalize_and_output_int(
-            task_category, quantization=0, partial_quantization=False
+            task_category, quantization=0, auto_quantization=False
         )
         assert skip is False
         assert output is False
@@ -364,7 +364,7 @@ def test_classification_quant_sets_output_int(self):
         """Classification with quantization should set output_int=True."""
         skip, output = constants.get_skip_normalize_and_output_int(
             constants.TASK_CATEGORY_TS_CLASSIFICATION,
-            quantization=1, partial_quantization=False,
+            quantization=1, auto_quantization=False,
         )
         assert skip is True
         assert output is True
@@ -373,7 +373,7 @@ def test_regression_quant_no_output_int(self):
         """Regression with quantization should set output_int=False."""
         skip, output = constants.get_skip_normalize_and_output_int(
             constants.TASK_CATEGORY_TS_REGRESSION,
-            quantization=1, partial_quantization=False,
+            quantization=1, auto_quantization=False,
         )
         assert skip is True
         assert output is False
@@ -382,16 +382,16 @@ def test_forecasting_quant_no_output_int(self):
         """Forecasting with quantization should set output_int=False."""
         skip, output = constants.get_skip_normalize_and_output_int(
             constants.TASK_CATEGORY_TS_FORECASTING,
-            quantization=1, partial_quantization=False,
+            quantization=1, auto_quantization=False,
         )
         assert skip is True
         assert output is False
 
-    def test_partial_quant_regression_override(self):
-        """Partial quantization for regression should set skip_normalize=False."""
+    def test_auto_quant_regression_override(self):
+        """Auto quantization for regression should set skip_normalize=False."""
         skip, output = constants.get_skip_normalize_and_output_int(
             constants.TASK_CATEGORY_TS_REGRESSION,
-            quantization=1, partial_quantization=True,
+            quantization=1, auto_quantization=True,
         )
         assert skip is False
         assert output is False
diff --git a/tinyml-modelmaker/tests/test_dataset_utils.py b/tinyml-modelmaker/tests/test_dataset_utils.py
index e098711..895c564 100644
--- a/tinyml-modelmaker/tests/test_dataset_utils.py
+++ b/tinyml-modelmaker/tests/test_dataset_utils.py
@@ -58,7 +58,7 @@ def test_split_factor_too_large(self, tmp_path):
         fl = tmp_path / "file_list.txt"
         fl.write_text("a.csv\nb.csv\n")
         split_files = (str(tmp_path / "train.txt"), str(tmp_path / "val.txt"))
-        with pytest.raises(ValueError, match="less than 1"):
+        with pytest.raises(ValueError, match=r"range \(0\.0, 1\.0\)"):
             dataset_utils.create_inter_file_split(str(fl), split_files, 1.5)
 
     def test_split_factor_list_sum_too_large(self, tmp_path):