diff --git a/tests/use_case/ad/InferenceTestAD.cc b/tests/use_case/ad/InferenceTestAD.cc
index b87699d..d5e21c2 100644
--- a/tests/use_case/ad/InferenceTestAD.cc
+++ b/tests/use_case/ad/InferenceTestAD.cc
@@ -19,7 +19,7 @@
 #include <random>
 
 #include "AdModel.hpp"
-#include "AdGoldenInput.hpp"
+#include "TestData_ad.hpp"
 #include "hal.h"
 #include "TensorFlowLiteMicro.hpp"
 
@@ -27,6 +27,8 @@
 #define AD_IN_FEATURE_VEC_DATA_SIZE (1024)
 #endif /* AD_FEATURE_VEC_DATA_SIZE */
 
+using namespace test;
+
 bool RunInference(arm::app::Model& model, const int8_t vec[])
 {
     TfLiteTensor *inputTensor = model.GetInputTensor(0);
@@ -67,7 +69,7 @@
     TfLiteTensor *outputTensor = model.GetOutputTensor(0);
 
     REQUIRE(outputTensor);
-    REQUIRE(outputTensor->bytes == AD_OUT_FEATURE_VEC_DATA_SIZE);
+    REQUIRE(outputTensor->bytes == OFM_DATA_SIZE);
     auto tensorData = tflite::GetTensorData<T>(outputTensor);
     REQUIRE(tensorData);
 
@@ -77,7 +79,7 @@
     }
 }
 
-TEST_CASE("Running random inference with TensorFlow Lite Micro and AdModel Int8", "[AD][.]")
+TEST_CASE("Running random inference with TensorFlow Lite Micro and AdModel Int8", "[AD]")
 {
     arm::app::AdModel model{};
 
@@ -88,13 +90,22 @@
     REQUIRE(RunInferenceRandom(model));
 }
 
-TEST_CASE("Running golden vector inference with TensorFlow Lite Micro and AdModel Int8", "[AD][.]")
+TEST_CASE("Running golden vector inference with TensorFlow Lite Micro and AdModel Int8", "[AD]")
 {
-    arm::app::AdModel model{};
+    for (uint32_t i = 0 ; i < NUMBER_OF_FM_FILES; ++i) {
+        auto input_goldenFV = get_ifm_data_array(i);;
+        auto output_goldenFV = get_ofm_data_array(i);
 
-    REQUIRE_FALSE(model.IsInited());
-    REQUIRE(model.Init());
-    REQUIRE(model.IsInited());
+        DYNAMIC_SECTION("Executing inference with re-init")
+        {
+            arm::app::AdModel model{};
 
-    TestInference(ad_golden_input, ad_golden_out, model);
+            REQUIRE_FALSE(model.IsInited());
+            REQUIRE(model.Init());
+            REQUIRE(model.IsInited());
+
+            TestInference<int8_t>(input_goldenFV, output_goldenFV, model);
+
+        }
+    }
 }
\ No newline at end of file
diff --git a/tests/use_case/ad/include/AdGoldenInput.hpp b/tests/use_case/ad/include/AdGoldenInput.hpp
deleted file mode 100644
index 41d1a89..0000000
--- a/tests/use_case/ad/include/AdGoldenInput.hpp
+++ /dev/null
@@ -1,132 +0,0 @@
-/*
- * Copyright (c) 2021 Arm Limited. All rights reserved.
- * SPDX-License-Identifier: Apache-2.0
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-#ifndef AD_GOLDEN_OUTPUTS_HPP
-#define AD_GOLDEN_OUTPUTS_HPP
-
-#include "Model.hpp"
-
-#ifdef __cplusplus
-extern "C" {
-#endif
-
-#include <stdint.h>
-
-#ifndef AD_FEATURE_VEC_DATA_SIZE
-#define AD_IN_FEATURE_VEC_DATA_SIZE       (1024)
-#define AD_OUT_FEATURE_VEC_DATA_SIZE       (8)
-#endif /* AD_FEATURE_VEC_DATA_SIZE */
-
-/* Golden input. */
-uint8_t ad_golden_input[AD_IN_FEATURE_VEC_DATA_SIZE] = {
-  0x7a, 0x7c, 0x7f, 0x7c, 0x7b, 0x61, 0x7f, 0x75, 0x7f, 0x6b, 0x6d, 0x71,
-  0x7f, 0x6e, 0x7a, 0x76, 0x7f, 0x7f, 0x65, 0x7f, 0x7f, 0x6f, 0x5d, 0x67,
-  0x7f, 0x5b, 0x7a, 0x43, 0x65, 0x69, 0x4e, 0x63, 0x5f, 0x56, 0x4e, 0x64,
-  0x36, 0x4a, 0x3c, 0x56, 0x3a, 0x61, 0x71, 0x74, 0x72, 0x6f, 0x71, 0x71,
-  0x66, 0x7b, 0x68, 0x62, 0x44, 0x5f, 0x2f, 0x3d, 0x56, 0x5b, 0x5b, 0x4d,
-  0x5f, 0x59, 0x58, 0x6e, 0x4f, 0x3d, 0x48, 0x5f, 0x46, 0x38, 0x48, 0x4f,
-  0x46, 0x74, 0x6d, 0x61, 0x60, 0x63, 0x6a, 0x68, 0x62, 0x69, 0x63, 0x5c,
-  0x6e, 0x4d, 0x4c, 0x3c, 0x5a, 0x55, 0x4a, 0x5d, 0x59, 0x66, 0x67, 0x6c,
-  0x55, 0x40, 0x49, 0x47, 0x56, 0x61, 0x48, 0x4d, 0x64, 0x61, 0x77, 0x7e,
-  0x37, 0x63, 0x52, 0x3e, 0x57, 0x4d, 0x54, 0x4f, 0x3b, 0x4c, 0x54, 0x50,
-  0x55, 0x4c, 0x57, 0x58, 0x45, 0x7b, 0x74, 0x58, 0x39, 0x34, 0x3c, 0x38,
-  0x3e, 0x1e, 0x22, 0x46, 0x2c, 0x7a, 0x6e, 0x74, 0x72, 0x70, 0x61, 0x7d,
-  0x69, 0x79, 0x66, 0x3c, 0x33, 0x20, 0x3a, 0x20, 0x34, 0x29, 0x3c, 0x4e,
-  0x47, 0x5b, 0x78, 0x47, 0x36, 0x30, 0x18, 0x45, 0x24, 0x25, 0x2c, 0x75,
-  0x71, 0x70, 0x7f, 0x73, 0x6c, 0x6c, 0x77, 0x6a, 0x6d, 0x6b, 0x6d, 0x5b,
-  0x36, 0x43, 0x34, 0x2b, 0x2e, 0x3b, 0x32, 0x67, 0x2a, 0x5b, 0x7f, 0x66,
-  0x32, 0x24, 0x28, 0x29, 0x2d, 0x31, 0x2b, 0x1d, 0x0d, 0x40, 0x3a, 0x49,
-  0x3b, 0x42, 0x37, 0x43, 0x40, 0x44, 0x4f, 0x40, 0x25, 0x1b, 0x33, 0x32,
-  0x15, 0x3b, 0x22, 0x33, 0x45, 0x4e, 0x45, 0x3a, 0x2a, 0x10, 0x19, 0x3a,
-  0x27, 0x25, 0x18, 0x0d, 0x0d, 0x3a, 0x36, 0x2d, 0x21, 0x34, 0x25, 0x38,
-  0x26, 0x33, 0x2f, 0x33, 0x2a, 0x21, 0x36, 0x1e, 0x2b, 0x28, 0x29, 0x31,
-  0x25, 0x2e, 0x4d, 0x32, 0x42, 0x1b, 0x37, 0x1a, 0x34, 0x36, 0x23, 0x25,
-  0x2b, 0x3f, 0x46, 0x41, 0x4c, 0x35, 0x39, 0x2d, 0x37, 0x4d, 0x42, 0x46,
-  0x27, 0x36, 0x20, 0x34, 0x10, 0x32, 0x19, 0x21, 0x33, 0x3b, 0x39, 0x46,
-  0x10, 0xf3, 0x26, 0x13, 0x24, 0x1f, 0x28, 0x18, 0x29, 0x20, 0x20, 0x14,
-  0x1f, 0x17, 0x27, 0x34, 0x38, 0x3e, 0x26, 0x37, 0x20, 0x33, 0x16, 0x26,
-  0x0e, 0x1c, 0x31, 0x1d, 0x23, 0x2e, 0x44, 0x38, 0x25, 0x2f, 0x27, 0x39,
-  0x3b, 0x2b, 0x36, 0x3c, 0x35, 0x3f, 0x2d, 0x3f, 0x42, 0x32, 0x43, 0x4e,
-  0x55, 0x3d, 0x17, 0x2e, 0x39, 0x20, 0x31, 0x41, 0x38, 0x2b, 0x31, 0x38,
-  0x46, 0x3f, 0x1e, 0x2d, 0x0a, 0x07, 0x18, 0xfc, 0x1a, 0x14, 0xec, 0x25,
-  0x1e, 0x30, 0x3c, 0x37, 0x2a, 0x47, 0x3c, 0x3b, 0x3b, 0x37, 0x2b, 0x22,
-  0x18, 0x1b, 0x31, 0x1e, 0x0e, 0x22, 0x13, 0x11, 0x10, 0x10, 0x14, 0x22,
-  0x0c, 0x0e, 0x18, 0x03, 0x0e, 0x03, 0x03, 0x08, 0x26, 0x0c, 0x1a, 0x0a,
-  0x06, 0x2d, 0x1e, 0x1e, 0x14, 0x1a, 0x26, 0x1d, 0x06, 0x06, 0x1c, 0x0e,
-  0x16, 0x06, 0x09, 0x13, 0x1c, 0x21, 0x25, 0x0d, 0x1c, 0x00, 0xfa, 0xfd,
-  0x13, 0xfa, 0x18, 0xff, 0x0d, 0x08, 0x23, 0x2e, 0x26, 0x1d, 0x14, 0x10,
-  0x14, 0x28, 0x14, 0x1b, 0x05, 0x0a, 0xff, 0xfa, 0x1a, 0x18, 0x11, 0x13,
-  0x16, 0x0f, 0x07, 0x12, 0x05, 0x00, 0x13, 0xf3, 0x05, 0x01, 0x01, 0x01,
-  0x1a, 0x16, 0x2b, 0x26, 0x1e, 0x21, 0x15, 0x13, 0x12, 0x28, 0x19, 0x1c,
-  0xff, 0xf8, 0xf0, 0x02, 0x01, 0x05, 0x04, 0x19, 0x11, 0x14, 0x1b, 0x15,
-  0xea, 0x19, 0x12, 0x02, 0x0f, 0x11, 0xee, 0xfe, 0x1c, 0x2f, 0x19, 0x38,
-  0x2a, 0x30, 0x26, 0x1e, 0x28, 0x29, 0x24, 0x12, 0x01, 0x12, 0xff, 0x0c,
-  0x09, 0x0b, 0x26, 0x24, 0x21, 0x24, 0x11, 0x21, 0x13, 0x17, 0xf8, 0x0c,
-  0xfd, 0x03, 0xf9, 0xfc, 0x03, 0x20, 0x14, 0x34, 0x1e, 0x30, 0x2e, 0x25,
-  0x23, 0x29, 0x16, 0x01, 0xf4, 0x05, 0x15, 0x05, 0xf9, 0x02, 0xea, 0x32,
-  0x38, 0x28, 0x28, 0x18, 0xf6, 0xfa, 0xfb, 0xff, 0xf9, 0xee, 0xff, 0x01,
-  0xfc, 0x41, 0x40, 0x2b, 0x2f, 0x1f, 0x1c, 0x20, 0x21, 0x28, 0x2b, 0x17,
-  0xfd, 0xf9, 0x07, 0xf5, 0x01, 0xf8, 0xfe, 0xfe, 0x11, 0x14, 0x27, 0x0e,
-  0xf5, 0xfd, 0xe7, 0x05, 0xef, 0xee, 0xe9, 0xf6, 0xff, 0x10, 0x0c, 0x16,
-  0x15, 0x16, 0x0d, 0x1c, 0x15, 0x1c, 0x09, 0xf6, 0x00, 0xfe, 0xf4, 0xf8,
-  0xe1, 0x0a, 0xfa, 0x05, 0x0b, 0x1b, 0x19, 0x05, 0xf0, 0xec, 0xec, 0x02,
-  0xf0, 0xec, 0xf4, 0xec, 0xe7, 0x30, 0x47, 0x2d, 0x31, 0x2a, 0x24, 0x31,
-  0x1f, 0x31, 0x2c, 0x07, 0xe4, 0xfa, 0xef, 0xee, 0xfe, 0xf5, 0xf1, 0x1a,
-  0x18, 0x33, 0x1c, 0x10, 0xf5, 0xce, 0xeb, 0xe3, 0xf1, 0xec, 0xe7, 0xed,
-  0xde, 0x19, 0x2e, 0x11, 0x1f, 0x17, 0x19, 0x23, 0x17, 0x1d, 0x1b, 0x01,
-  0xef, 0xed, 0xeb, 0xf8, 0xe9, 0xf0, 0xf3, 0x1c, 0x19, 0x2a, 0x0d, 0x19,
-  0xe3, 0xe1, 0xee, 0xe0, 0xe7, 0xee, 0xe7, 0xee, 0xea, 0x30, 0x2e, 0x2f,
-  0x32, 0x11, 0x29, 0x38, 0x0f, 0x1a, 0x29, 0x24, 0xe6, 0xfa, 0xfc, 0xf0,
-  0xed, 0xec, 0xe1, 0x2e, 0x13, 0x29, 0x22, 0x16, 0xd4, 0xee, 0xeb, 0xee,
-  0xd3, 0xe4, 0xe4, 0xe5, 0xee, 0x23, 0x08, 0x10, 0x15, 0x17, 0x1b, 0x2b,
-  0x1b, 0x1d, 0x17, 0x03, 0xf8, 0xdd, 0xe3, 0xe8, 0xe5, 0xd8, 0xdb, 0x09,
-  0xf5, 0x10, 0x16, 0x14, 0xd9, 0xde, 0xd0, 0xd7, 0xd7, 0xda, 0xe0, 0xe1,
-  0xe4, 0x0f, 0x17, 0x04, 0x10, 0x0c, 0x14, 0x1d, 0x1d, 0x17, 0x15, 0xfa,
-  0xd9, 0xd6, 0xe1, 0xdf, 0xd7, 0xdf, 0xd5, 0x18, 0xf5, 0x14, 0x08, 0x0b,
-  0xd0, 0xd6, 0xd4, 0xd7, 0xc6, 0xda, 0xc5, 0xda, 0xdc, 0x14, 0x26, 0x15,
-  0x19, 0x0d, 0x0b, 0x0f, 0x07, 0x09, 0x1b, 0x03, 0xdc, 0xda, 0xd6, 0xd8,
-  0xc0, 0xc5, 0xdc, 0x08, 0xfb, 0x10, 0x0d, 0x13, 0xd8, 0xde, 0xcb, 0xd6,
-  0xd0, 0xc7, 0xcd, 0xdc, 0xc3, 0x0c, 0x0f, 0x08, 0x13, 0x13, 0x25, 0x25,
-  0x13, 0x1f, 0x11, 0xee, 0xd0, 0xd0, 0xd2, 0xcd, 0xbf, 0xca, 0xd2, 0x0a,
-  0xeb, 0x04, 0x03, 0x10, 0xd0, 0xcd, 0xb1, 0xc7, 0xca, 0xbf, 0xe1, 0xdd,
-  0xce, 0x2b, 0x19, 0x20, 0x20, 0x14, 0x24, 0x34, 0x27, 0x2c, 0x25, 0xf8,
-  0xd5, 0xc7, 0xcb, 0xba, 0xc0, 0xcf, 0xc4, 0x14, 0x06, 0x1f, 0x28, 0x10,
-  0xc9, 0xc9, 0xc3, 0xbf, 0xc4, 0xcd, 0xd2, 0xcc, 0xd4, 0x15, 0x27, 0x1e,
-  0x19, 0x05, 0x18, 0x1d, 0x24, 0x1a, 0x1f, 0xf9, 0xcc, 0xd3, 0xc3, 0xcd,
-  0xcc, 0xc1, 0xd5, 0x10, 0xe7, 0x1d, 0x12, 0x04, 0xb4, 0xb9, 0xb0, 0xb9,
-  0xb1, 0xb1, 0xbb, 0xd2, 0xb0, 0xff, 0x22, 0x06, 0xff, 0xf7, 0xfb, 0x07,
-  0xf8, 0xfa, 0x03, 0xef, 0xc2, 0xc7, 0xb9, 0xbb, 0xb4, 0xb2, 0xb5, 0xf2,
-  0xcc, 0x05, 0xf1, 0xea, 0xb0, 0xb1, 0xa7, 0xab, 0xa9, 0xa6, 0xb2, 0xbf,
-  0xb4, 0x04, 0x0f, 0x02, 0x0e, 0x0a, 0x05, 0x07, 0xff, 0x04, 0x0a, 0xe2,
-  0xac, 0xad, 0xa9, 0xa0, 0xa8, 0xa3, 0x9a, 0xef, 0xd3, 0xf5, 0x03, 0xfd,
-  0x9c, 0x99, 0x99, 0x9c, 0x96, 0x99, 0xaf, 0xa8, 0xaa, 0xfd, 0x09, 0x0e,
-  0xf5, 0xed, 0xe7, 0xf4, 0xec, 0xf4, 0xf1, 0xd5, 0xa5, 0x9a, 0x9e, 0x98,
-  0xa7, 0x99, 0xa2, 0xd9, 0xc2, 0xf1, 0xee, 0xec, 0x8a, 0x86, 0x8c, 0x8d,
-  0x84, 0x88, 0xa0, 0xad, 0xa2, 0xe5, 0x02, 0xff, 0xf5, 0xe4, 0xee, 0xf1,
-  0xf2, 0xec, 0xf0, 0xc9, 0x9e, 0x97, 0x98, 0x89, 0x8f, 0x88, 0x93, 0xd9,
-  0xd1, 0xf8, 0xeb, 0xde
-};
-
-/* Golden output */
-uint8_t ad_golden_out[AD_OUT_FEATURE_VEC_DATA_SIZE] = {
-        0x3a, 0x7f, 0x36, 0x76, 0x80, 0x80, 0x80, 0x80
-};
-
-#ifdef __cplusplus
-}
-#endif
-
-#endif /* AD_GOLDEN_OUTPUTS_HPP */
diff --git a/tests/use_case/asr/InferenceTestWav2Letter.cc b/tests/use_case/asr/InferenceTestWav2Letter.cc
index 1fa4092..0943db8 100644
--- a/tests/use_case/asr/InferenceTestWav2Letter.cc
+++ b/tests/use_case/asr/InferenceTestWav2Letter.cc
@@ -22,6 +22,8 @@
 #include <catch.hpp>
 #include <random>
 
+using namespace test;
+
 bool RunInference(arm::app::Model& model, const int8_t vec[], const size_t copySz)
 {
     TfLiteTensor* inputTensor = model.GetInputTensor(0);
diff --git a/tests/use_case/img_class/InferenceTestMobilenetV2.cc b/tests/use_case/img_class/InferenceTestMobilenetV2.cc
index 698382f..b2720a8 100644
--- a/tests/use_case/img_class/InferenceTestMobilenetV2.cc
+++ b/tests/use_case/img_class/InferenceTestMobilenetV2.cc
@@ -22,6 +22,7 @@
 
 #include <catch.hpp>
 
+using namespace test;
 
 bool RunInference(arm::app::Model& model, const uint8_t imageData[])
 {
diff --git a/tests/use_case/kws/InferenceTestDSCNN.cc b/tests/use_case/kws/InferenceTestDSCNN.cc
index 06358a4..d02e33c 100644
--- a/tests/use_case/kws/InferenceTestDSCNN.cc
+++ b/tests/use_case/kws/InferenceTestDSCNN.cc
@@ -22,6 +22,8 @@
 #include <catch.hpp>
 #include <random>
 
+using namespace test;
+
 bool RunInference(arm::app::Model& model, const int8_t vec[])
 {
     TfLiteTensor* inputTensor = model.GetInputTensor(0);
diff --git a/tests/use_case/kws_asr/InferenceTestDSCNN.cc b/tests/use_case/kws_asr/InferenceTestDSCNN.cc
index f0e5c02..e210c33 100644
--- a/tests/use_case/kws_asr/InferenceTestDSCNN.cc
+++ b/tests/use_case/kws_asr/InferenceTestDSCNN.cc
@@ -22,34 +22,32 @@
 #include <catch.hpp>
 #include <random>
 
-namespace arm {
-namespace app {
+namespace test {
 namespace kws {
-bool RunInference(arm::app::Model& model, const int8_t vec[])
-{
+
+bool RunInference(arm::app::Model& model, const int8_t vec[]) {
     TfLiteTensor* inputTensor = model.GetInputTensor(0);
     REQUIRE(inputTensor);
 
     const size_t copySz = inputTensor->bytes < IFM_DATA_SIZE ?
-                            inputTensor->bytes :
-                            IFM_DATA_SIZE;
+                          inputTensor->bytes :
+                          IFM_DATA_SIZE;
     memcpy(inputTensor->data.data, vec, copySz);
 
     return model.RunInference();
 }
 
-bool RunInferenceRandom(arm::app::Model& model)
-{
+bool RunInferenceRandom(arm::app::Model& model) {
     TfLiteTensor* inputTensor = model.GetInputTensor(0);
     REQUIRE(inputTensor);
 
     std::random_device rndDevice;
     std::mt19937 mersenneGen{rndDevice()};
-    std::uniform_int_distribution<short> dist {-128, 127};
+    std::uniform_int_distribution<short> dist{-128, 127};
 
-    auto gen = [&dist, &mersenneGen](){
-                   return dist(mersenneGen);
-               };
+    auto gen = [&dist, &mersenneGen]() {
+        return dist(mersenneGen);
+    };
 
     std::vector<int8_t> randomAudio(inputTensor->bytes);
     std::generate(std::begin(randomAudio), std::end(randomAudio), gen);
@@ -59,8 +57,7 @@
 }
 
 template<typename T>
-void TestInference(const T* input_goldenFV, const T* output_goldenFV, arm::app::Model& model)
-{
+void TestInference(const T* input_goldenFV, const T* output_goldenFV, arm::app::Model& model) {
     REQUIRE(RunInference(model, input_goldenFV));
 
     TfLiteTensor* outputTensor = model.GetOutputTensor(0);
@@ -71,12 +68,11 @@
     REQUIRE(tensorData);
 
     for (size_t i = 0; i < outputTensor->bytes; i++) {
-        REQUIRE((int)tensorData[i] == (int)((T)output_goldenFV[i]));
+        REQUIRE((int) tensorData[i] == (int) ((T) output_goldenFV[i]));
     }
 }
 
-TEST_CASE("Running random inference with Tflu and DsCnnModel Int8", "[DS_CNN]")
-{
+TEST_CASE("Running random inference with Tflu and DsCnnModel Int8", "[DS_CNN]") {
     arm::app::DsCnnModel model{};
 
     REQUIRE_FALSE(model.IsInited());
@@ -86,14 +82,12 @@
     REQUIRE(RunInferenceRandom(model));
 }
 
-TEST_CASE("Running inference with Tflu and DsCnnModel Uint8", "[DS_CNN]")
-{
-    for (uint32_t i = 0 ; i < NUMBER_OF_FM_FILES; ++i) {
+TEST_CASE("Running inference with Tflu and DsCnnModel Uint8", "[DS_CNN]") {
+    for (uint32_t i = 0; i < NUMBER_OF_FM_FILES; ++i) {
         const int8_t* input_goldenFV = get_ifm_data_array(i);
         const int8_t* output_goldenFV = get_ofm_data_array(i);
 
-        DYNAMIC_SECTION("Executing inference with re-init")
-        {
+        DYNAMIC_SECTION("Executing inference with re-init") {
             arm::app::DsCnnModel model{};
 
             REQUIRE_FALSE(model.IsInited());
@@ -107,5 +101,4 @@
 }
 
 } //namespace
-} //namespace
-} //namespace
+} //namespace
\ No newline at end of file
diff --git a/tests/use_case/kws_asr/InferenceTestWav2Letter.cc b/tests/use_case/kws_asr/InferenceTestWav2Letter.cc
index ee63c2f..897ad0a 100644
--- a/tests/use_case/kws_asr/InferenceTestWav2Letter.cc
+++ b/tests/use_case/kws_asr/InferenceTestWav2Letter.cc
@@ -22,8 +22,7 @@
 #include <catch.hpp>
 #include <random>
 
-namespace arm {
-namespace app {
+namespace test {
 namespace asr {
 
 bool RunInference(arm::app::Model& model, const int8_t vec[], const size_t copySz)
@@ -111,4 +110,3 @@
 
 } //namespace
 } //namespace
-} //namespace