MLECO-3183: Refactoring application sources

Platform agnostic application sources are moved into application
api module with their own independent CMake projects.

Changes for MLECO-3080 also included - they create CMake projects
individial API's (again, platform agnostic) that dependent on the
common logic. The API for KWS_API "joint" API has been removed and
now the use case relies on individual KWS, and ASR API libraries.

Change-Id: I1f7748dc767abb3904634a04e0991b74ac7b756d
Signed-off-by: Kshitij Sisodia <kshitij.sisodia@arm.com>

10 files changed, 26 insertions, 1293 deletions

diff --git a/source/use_case/ad/include/AdMelSpectrogram.hpp b/source/use_case/ad/include/AdMelSpectrogram.hpp
deleted file mode 100644
index 05c5bfc..0000000
--- a/source/use_case/ad/include/AdMelSpectrogram.hpp
+++ /dev/null
@@ -1,97 +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 ADMELSPECTROGRAM_HPP
-#define ADMELSPECTROGRAM_HPP
-
-#include "MelSpectrogram.hpp"
-
-namespace arm {
-namespace app {
-namespace audio {
-
-    /* Class to provide anomaly detection specific Mel Spectrogram calculation requirements */
-    class AdMelSpectrogram : public MelSpectrogram {
-
-    public:
-        static constexpr uint32_t  ms_defaultSamplingFreq = 16000;
-        static constexpr uint32_t  ms_defaultNumFbankBins =    64;
-        static constexpr uint32_t  ms_defaultMelLoFreq    =     0;
-        static constexpr uint32_t  ms_defaultMelHiFreq    =  8000;
-        static constexpr bool      ms_defaultUseHtkMethod = false;
-
-        explicit AdMelSpectrogram(const size_t frameLen)
-                :  MelSpectrogram(MelSpecParams(
-                ms_defaultSamplingFreq, ms_defaultNumFbankBins,
-                ms_defaultMelLoFreq, ms_defaultMelHiFreq,
-                frameLen, ms_defaultUseHtkMethod))
-        {}
-
-        AdMelSpectrogram()  = delete;
-        ~AdMelSpectrogram() = default;
-
-    protected:
-
-        /**
-         * @brief       Overrides base class implementation of this function.
-         * @param[in]   fftVec                  Vector populated with FFT magnitudes
-         * @param[in]   melFilterBank           2D Vector with filter bank weights
-         * @param[in]   filterBankFilterFirst   Vector containing the first indices of filter bank
-         *                                      to be used for each bin.
-         * @param[in]   filterBankFilterLast    Vector containing the last indices of filter bank
-         *                                      to be used for each bin.
-         * @param[out]  melEnergies             Pre-allocated vector of MEL energies to be
-         *                                      populated.
-         * @return      true if successful, false otherwise
-         */
-        virtual bool ApplyMelFilterBank(
-                std::vector<float>&                 fftVec,
-                std::vector<std::vector<float>>&    melFilterBank,
-                std::vector<uint32_t>&               filterBankFilterFirst,
-                std::vector<uint32_t>&               filterBankFilterLast,
-                std::vector<float>&                 melEnergies) override;
-
-        /**
-         * @brief       Override for the base class implementation convert mel
-         *              energies to logarithmic scale. The difference from
-         *              default behaviour is that the power is converted to dB
-         *              and subsequently clamped.
-         * @param[in,out]   melEnergies - 1D vector of Mel energies
-         **/
-        virtual void ConvertToLogarithmicScale(std::vector<float>& melEnergies) override;
-
-        /**
-         * @brief       Given the low and high Mel values, get the normaliser
-         *              for weights to be applied when populating the filter
-         *              bank. Override for the base class implementation.
-         * @param[in]   leftMel - low Mel frequency value
-         * @param[in]   rightMel - high Mel frequency value
-         * @param[in]   useHTKMethod - bool to signal if HTK method is to be
-         *              used for calculation
-         * @return      Return float value to be applied 
-         *              when populating the filter bank.
-         */
-        virtual float GetMelFilterBankNormaliser(
-                const float&   leftMel,
-                const float&   rightMel,
-                const bool     useHTKMethod) override;
-    };
-
-} /* namespace audio */
-} /* namespace app */
-} /* namespace arm */
-
-#endif /* ADMELSPECTROGRAM_HPP */
diff --git a/source/use_case/ad/include/AdModel.hpp b/source/use_case/ad/include/AdModel.hpp
deleted file mode 100644
index 2195a7c..0000000
--- a/source/use_case/ad/include/AdModel.hpp
+++ /dev/null
@@ -1,59 +0,0 @@
-/*
- * Copyright (c) 2021-2022 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_MODEL_HPP
-#define AD_MODEL_HPP
-
-#include "Model.hpp"
-
-extern const int g_FrameLength;
-extern const int g_FrameStride;
-extern const float g_ScoreThreshold;
-extern const float g_TrainingMean;
-
-namespace arm {
-namespace app {
-
-    class AdModel : public Model {
-
-    public:
-        /* Indices for the expected model - based on input tensor shape */
-        static constexpr uint32_t ms_inputRowsIdx = 1;
-        static constexpr uint32_t ms_inputColsIdx = 2;
-
-    protected:
-        /** @brief   Gets the reference to op resolver interface class */
-        const tflite::MicroOpResolver& GetOpResolver() override;
-
-        /** @brief   Adds operations to the op resolver instance */
-        bool EnlistOperations() override;
-
-        const uint8_t* ModelPointer() override;
-
-        size_t ModelSize() override;
-
-    private:
-        /* Maximum number of individual operations that can be enlisted */
-        static constexpr int ms_maxOpCnt = 6;
-
-        /* A mutable op resolver instance */
-        tflite::MicroMutableOpResolver<ms_maxOpCnt> m_opResolver;
-    };
-
-} /* namespace app */
-} /* namespace arm */
-
-#endif /* AD_MODEL_HPP */
diff --git a/source/use_case/ad/include/AdProcessing.hpp b/source/use_case/ad/include/AdProcessing.hpp
deleted file mode 100644
index 9abf6f1..0000000
--- a/source/use_case/ad/include/AdProcessing.hpp
+++ /dev/null
@@ -1,230 +0,0 @@
-/*
- * Copyright (c) 2022 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_PROCESSING_HPP
-#define AD_PROCESSING_HPP
-
-#include "BaseProcessing.hpp"
-#include "AudioUtils.hpp"
-#include "AdMelSpectrogram.hpp"
-#include "log_macros.h"
-
-namespace arm {
-namespace app {
-
-    /**
-     * @brief   Pre-processing class for anomaly detection use case.
-     *          Implements methods declared by BasePreProcess and anything else needed
-     *          to populate input tensors ready for inference.
-     */
-    class AdPreProcess : public BasePreProcess {
-
-    public:
-        /**
-         * @brief Constructor for AdPreProcess class objects
-         * @param[in] inputTensor  input tensor pointer from the tensor arena.
-         * @param[in] melSpectrogramFrameLen MEL spectrogram's frame length
-         * @param[in] melSpectrogramFrameStride MEL spectrogram's frame stride
-         * @param[in] adModelTrainingMean Training mean for the Anomaly detection model being used.
-         */
-        explicit AdPreProcess(TfLiteTensor* inputTensor,
-                              uint32_t melSpectrogramFrameLen,
-                              uint32_t melSpectrogramFrameStride,
-                              float adModelTrainingMean);
-
-        ~AdPreProcess() = default;
-
-        /**
-         * @brief Function to invoke pre-processing and populate the input vector
-         * @param input pointer to input data. For anomaly detection, this is the pointer to
-         *              the audio data.
-         * @param inputSize Size of the data being passed in for pre-processing.
-         * @return True if successful, false otherwise.
-         */
-        bool DoPreProcess(const void* input, size_t inputSize) override;
-
-        /**
-         * @brief Getter function for audio window size computed when constructing
-         *        the class object.
-         * @return Audio window size as 32 bit unsigned integer.
-         */
-        uint32_t GetAudioWindowSize();
-
-        /**
-         * @brief Getter function for audio window stride computed when constructing
-         *        the class object.
-         * @return Audio window stride as 32 bit unsigned integer.
-         */
-        uint32_t GetAudioDataStride();
-
-        /**
-         * @brief Setter function for current audio index. This is only used for evaluating
-         *        if previously computed features can be re-used from cache.
-         */
-        void SetAudioWindowIndex(uint32_t idx);
-
-    private:
-        bool        m_validInstance{false}; /**< Indicates the current object is valid. */
-        uint32_t    m_melSpectrogramFrameLen{}; /**< MEL spectrogram's window frame length */
-        uint32_t    m_melSpectrogramFrameStride{}; /**< MEL spectrogram's window frame stride */
-        uint8_t     m_inputResizeScale{}; /**< Downscaling factor for the MEL energy matrix. */
-        uint32_t    m_numMelSpecVectorsInAudioStride{};  /**< Number of frames to move across the audio. */
-        uint32_t    m_audioDataWindowSize{}; /**< Audio window size computed based on other parameters. */
-        uint32_t    m_audioDataStride{}; /**< Audio window stride computed. */
-        uint32_t    m_numReusedFeatureVectors{}; /**< Number of MEL vectors that can be re-used */
-        uint32_t    m_audioWindowIndex{}; /**< Current audio window index (from audio's sliding window) */
-
-        audio::SlidingWindow<const int16_t> m_melWindowSlider; /**< Internal MEL spectrogram window slider */
-        audio::AdMelSpectrogram m_melSpec; /**< MEL spectrogram computation object */
-        std::function<void
-            (std::vector<int16_t>&, int, bool, size_t, size_t)> m_featureCalc; /**< Feature calculator object */
-    };
-
-    class AdPostProcess : public BasePostProcess {
-    public:
-        /**
-         * @brief Constructor for AdPostProcess object.
-         * @param[in] outputTensor Output tensor pointer.
-         */
-        explicit AdPostProcess(TfLiteTensor* outputTensor);
-
-        ~AdPostProcess() = default;
-
-        /**
-         * @brief Function to do the post-processing on the output tensor.
-         * @return True if successful, false otherwise.
-         */
-        bool DoPostProcess() override;
-
-        /**
-         * @brief Getter function for an element from the de-quantised output vector.
-         * @param index Index of the element to be retrieved.
-         * @return index represented as a 32 bit floating point number.
-         */
-        float GetOutputValue(uint32_t index);
-
-    private:
-        TfLiteTensor* m_outputTensor{}; /**< Output tensor pointer */
-        std::vector<float> m_dequantizedOutputVec{}; /**< Internal output vector */
-
-        /**
-         * @brief De-quantizes and flattens the output tensor into a vector.
-         * @tparam T template parameter to indicate data type.
-         * @return True if successful, false otherwise.
-         */
-        template<typename T>
-        bool Dequantize()
-        {
-            TfLiteTensor* tensor = this->m_outputTensor;
-            if (tensor == nullptr) {
-                printf_err("Invalid output tensor.\n");
-                return false;
-            }
-            T* tensorData = tflite::GetTensorData<T>(tensor);
-
-            uint32_t totalOutputSize = 1;
-            for (int inputDim = 0; inputDim < tensor->dims->size; inputDim++){
-                totalOutputSize *= tensor->dims->data[inputDim];
-            }
-
-            /* For getting the floating point values, we need quantization parameters */
-            QuantParams quantParams = GetTensorQuantParams(tensor);
-
-            this->m_dequantizedOutputVec = std::vector<float>(totalOutputSize, 0);
-
-            for (size_t i = 0; i < totalOutputSize; ++i) {
-                this->m_dequantizedOutputVec[i] = quantParams.scale * (tensorData[i] - quantParams.offset);
-            }
-
-            return true;
-        }
-    };
-
-    /* Templated instances available: */
-    template bool AdPostProcess::Dequantize<int8_t>();
-
-    /**
-     * @brief Generic feature calculator factory.
-     *
-     * Returns lambda function to compute features using features cache.
-     * Real features math is done by a lambda function provided as a parameter.
-     * Features are written to input tensor memory.
-     *
-     * @tparam T            feature vector type.
-     * @param inputTensor   model input tensor pointer.
-     * @param cacheSize     number of feature vectors to cache. Defined by the sliding window overlap.
-     * @param compute       features calculator function.
-     * @return              lambda function to compute features.
-     */
-    template<class T>
-    std::function<void (std::vector<int16_t>&, size_t, bool, size_t, size_t)>
-    FeatureCalc(TfLiteTensor* inputTensor, size_t cacheSize,
-                std::function<std::vector<T> (std::vector<int16_t>& )> compute)
-    {
-        /* Feature cache to be captured by lambda function*/
-        static std::vector<std::vector<T>> featureCache = std::vector<std::vector<T>>(cacheSize);
-
-        return [=](std::vector<int16_t>& audioDataWindow,
-                   size_t index,
-                   bool useCache,
-                   size_t featuresOverlapIndex,
-                   size_t resizeScale)
-        {
-            T* tensorData = tflite::GetTensorData<T>(inputTensor);
-            std::vector<T> features;
-
-            /* Reuse features from cache if cache is ready and sliding windows overlap.
-             * Overlap is in the beginning of sliding window with a size of a feature cache. */
-            if (useCache && index < featureCache.size()) {
-                features = std::move(featureCache[index]);
-            } else {
-                features = std::move(compute(audioDataWindow));
-            }
-            auto size = features.size() / resizeScale;
-            auto sizeBytes = sizeof(T);
-
-            /* Input should be transposed and "resized" by skipping elements. */
-            for (size_t outIndex = 0; outIndex < size; outIndex++) {
-                std::memcpy(tensorData + (outIndex*size) + index, &features[outIndex*resizeScale], sizeBytes);
-            }
-
-            /* Start renewing cache as soon iteration goes out of the windows overlap. */
-            if (index >= featuresOverlapIndex / resizeScale) {
-                featureCache[index - featuresOverlapIndex / resizeScale] = std::move(features);
-            }
-        };
-    }
-
-    template std::function<void (std::vector<int16_t>&, size_t , bool, size_t, size_t)>
-    FeatureCalc<int8_t>(TfLiteTensor* inputTensor,
-                        size_t cacheSize,
-                        std::function<std::vector<int8_t> (std::vector<int16_t>&)> compute);
-
-    template std::function<void(std::vector<int16_t>&, size_t, bool, size_t, size_t)>
-    FeatureCalc<float>(TfLiteTensor *inputTensor,
-                       size_t cacheSize,
-                       std::function<std::vector<float>(std::vector<int16_t>&)> compute);
-
-    std::function<void (std::vector<int16_t>&, int, bool, size_t, size_t)>
-    GetFeatureCalculator(audio::AdMelSpectrogram& melSpec,
-                         TfLiteTensor* inputTensor,
-                         size_t cacheSize,
-                         float trainingMean);
-
-} /* namespace app */
-} /* namespace arm */
-
-#endif /* AD_PROCESSING_HPP */
diff --git a/source/use_case/ad/include/MelSpectrogram.hpp b/source/use_case/ad/include/MelSpectrogram.hpp
deleted file mode 100644
index d3ea3f7..0000000
--- a/source/use_case/ad/include/MelSpectrogram.hpp
+++ /dev/null
@@ -1,234 +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 MELSPECTROGRAM_HPP
-#define MELSPECTROGRAM_HPP
-
-#include "PlatformMath.hpp"
-
-#include <vector>
-#include <cstdint>
-#include <cmath>
-#include <limits>
-#include <string>
-
-namespace arm {
-namespace app {
-namespace audio {
-
-    /* Mel Spectrogram consolidated parameters */
-    class MelSpecParams {
-    public:
-        float       m_samplingFreq;
-        uint32_t    m_numFbankBins;
-        float       m_melLoFreq;
-        float       m_melHiFreq;
-        uint32_t    m_frameLen;
-        uint32_t    m_frameLenPadded;
-        bool        m_useHtkMethod;
-
-        /** @brief  Constructor */
-        MelSpecParams(const float samplingFreq, const uint32_t numFbankBins,
-                      const float melLoFreq, const float melHiFreq,
-                      const uint32_t frameLen, const bool useHtkMethod);
-
-        MelSpecParams()  = delete;
-        ~MelSpecParams() = default;
-
-        /** @brief  String representation of parameters */
-        std::string Str() const;
-    };
-
-    /**
-     * @brief   Class for Mel Spectrogram feature extraction.
-     *          Based on https://github.com/ARM-software/ML-KWS-for-MCU/blob/master/Deployment/Source/MFCC/mfcc.cpp
-     *          This class is designed to be generic and self-sufficient but
-     *          certain calculation routines can be overridden to accommodate
-     *          use-case specific requirements.
-     */
-    class MelSpectrogram {
-
-    public:
-        /**
-        * @brief        Extract Mel Spectrogram for one single small frame of
-        *               audio data e.g. 640 samples.
-        * @param[in]    audioData       Vector of audio samples to calculate
-        *               features for.
-        * @param[in]    trainingMean    Value to subtract from the the computed mel spectrogram, default 0.
-        * @return       Vector of extracted Mel Spectrogram features.
-        **/
-        std::vector<float> ComputeMelSpec(const std::vector<int16_t>& audioData, float trainingMean = 0);
-
-        /**
-         * @brief       Constructor
-         * @param[in]   params   Mel Spectrogram parameters
-        */
-        explicit MelSpectrogram(const MelSpecParams& params);
-
-        MelSpectrogram() = delete;
-        ~MelSpectrogram() = default;
-
-        /** @brief  Initialise */
-        void Init();
-
-        /**
-         * @brief        Extract Mel Spectrogram features and quantise for one single small
-         *               frame of audio data e.g. 640 samples.
-         * @param[in]    audioData      Vector of audio samples to calculate
-         *               features for.
-         * @param[in]    quantScale     quantisation scale.
-         * @param[in]    quantOffset    quantisation offset.
-         * @param[in]    trainingMean   training mean.
-         * @return       Vector of extracted quantised Mel Spectrogram features.
-         **/
-        template<typename T>
-        std::vector<T> MelSpecComputeQuant(const std::vector<int16_t>& audioData,
-                                           const float quantScale,
-                                           const int quantOffset,
-                                           float trainingMean = 0)
-        {
-            this->ComputeMelSpec(audioData, trainingMean);
-            float minVal = std::numeric_limits<T>::min();
-            float maxVal = std::numeric_limits<T>::max();
-
-            std::vector<T> melSpecOut(this->m_params.m_numFbankBins);
-            const size_t numFbankBins = this->m_params.m_numFbankBins;
-
-            /* Quantize to T. */
-            for (size_t k = 0; k < numFbankBins; ++k) {
-                auto quantizedEnergy = std::round(((this->m_melEnergies[k]) / quantScale) + quantOffset);
-                melSpecOut[k] = static_cast<T>(std::min<float>(std::max<float>(quantizedEnergy, minVal), maxVal));
-            }
-
-            return melSpecOut;
-        }
-
-        /* Constants */
-        static constexpr float ms_logStep = /*logf(6.4)*/ 1.8562979903656 / 27.0;
-        static constexpr float ms_freqStep = 200.0 / 3;
-        static constexpr float ms_minLogHz = 1000.0;
-        static constexpr float ms_minLogMel = ms_minLogHz / ms_freqStep;
-
-    protected:
-        /**
-         * @brief       Project input frequency to Mel Scale.
-         * @param[in]   freq          input frequency in floating point
-         * @param[in]   useHTKMethod  bool to signal if HTK method is to be
-         *                            used for calculation
-         * @return      Mel transformed frequency in floating point
-         **/
-        static float MelScale(const float    freq,
-                              const bool     useHTKMethod = true);
-
-        /**
-         * @brief       Inverse Mel transform - convert MEL warped frequency
-         *              back to normal frequency
-         * @param[in]   melFreq          Mel frequency in floating point
-         * @param[in]   useHTKMethod  bool to signal if HTK method is to be
-         *                            used for calculation
-         * @return      Real world frequency in floating point
-         **/
-        static float InverseMelScale(const float melFreq,
-                                     const bool  useHTKMethod = true);
-
-        /**
-         * @brief       Populates MEL energies after applying the MEL filter
-         *              bank weights and adding them up to be placed into
-         *              bins, according to the filter bank's first and last
-         *              indices (pre-computed for each filter bank element
-         *              by CreateMelFilterBank function).
-         * @param[in]   fftVec                  Vector populated with FFT magnitudes
-         * @param[in]   melFilterBank           2D Vector with filter bank weights
-         * @param[in]   filterBankFilterFirst   Vector containing the first indices of filter bank
-         *                                      to be used for each bin.
-         * @param[in]   filterBankFilterLast    Vector containing the last indices of filter bank
-         *                                      to be used for each bin.
-         * @param[out]  melEnergies             Pre-allocated vector of MEL energies to be
-         *                                      populated.
-         * @return      true if successful, false otherwise
-         */
-        virtual bool ApplyMelFilterBank(
-                std::vector<float>&                 fftVec,
-                std::vector<std::vector<float>>&    melFilterBank,
-                std::vector<uint32_t>&               filterBankFilterFirst,
-                std::vector<uint32_t>&               filterBankFilterLast,
-                std::vector<float>&                 melEnergies);
-
-        /**
-         * @brief           Converts the Mel energies for logarithmic scale
-         * @param[in,out]   melEnergies 1D vector of Mel energies
-         **/
-        virtual void ConvertToLogarithmicScale(std::vector<float>& melEnergies);
-
-        /**
-         * @brief       Given the low and high Mel values, get the normaliser
-         *              for weights to be applied when populating the filter
-         *              bank.
-         * @param[in]   leftMel      low Mel frequency value
-         * @param[in]   rightMel     high Mel frequency value
-         * @param[in]   useHTKMethod bool to signal if HTK method is to be
-         *                           used for calculation
-         * @return      Return float value to be applied 
-         *              when populating the filter bank.
-         */
-        virtual float GetMelFilterBankNormaliser(
-                const float&   leftMel,
-                const float&   rightMel,
-                const bool     useHTKMethod);
-
-    private:
-        MelSpecParams                   m_params;
-        std::vector<float>              m_frame;
-        std::vector<float>              m_buffer;
-        std::vector<float>              m_melEnergies;
-        std::vector<float>              m_windowFunc;
-        std::vector<std::vector<float>> m_melFilterBank;
-        std::vector<uint32_t>            m_filterBankFilterFirst;
-        std::vector<uint32_t>            m_filterBankFilterLast;
-        bool                            m_filterBankInitialised;
-        arm::app::math::FftInstance     m_fftInstance;
-
-        /**
-         * @brief       Initialises the filter banks.
-         **/
-        void InitMelFilterBank();
-
-        /**
-         * @brief       Signals whether the instance of MelSpectrogram has had its
-         *              required buffers initialised
-         * @return      True if initialised, false otherwise
-         **/
-        bool IsMelFilterBankInited() const;
-
-        /**
-         * @brief       Create mel filter banks for Mel Spectrogram calculation.
-         * @return      2D vector of floats
-         **/
-        std::vector<std::vector<float>> CreateMelFilterBank();
-
-        /**
-         * @brief       Computes the magnitude from an interleaved complex array
-         **/
-        void ConvertToPowerSpectrum();
-
-    };
-
-} /* namespace audio */
-} /* namespace app */
-} /* namespace arm */
-
-
-#endif /* MELSPECTROGRAM_HPP */
diff --git a/source/use_case/ad/src/AdMelSpectrogram.cc b/source/use_case/ad/src/AdMelSpectrogram.cc
deleted file mode 100644
index 14b9323..0000000
--- a/source/use_case/ad/src/AdMelSpectrogram.cc
+++ /dev/null
@@ -1,93 +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.
- */
-#include "AdMelSpectrogram.hpp"
-#include "PlatformMath.hpp"
-#include "log_macros.h"
-
-#include <cfloat>
-
-namespace arm {
-namespace app {
-namespace audio {
-
-    bool AdMelSpectrogram::ApplyMelFilterBank(
-            std::vector<float>&                 fftVec,
-            std::vector<std::vector<float>>&    melFilterBank,
-            std::vector<uint32_t>&               filterBankFilterFirst,
-            std::vector<uint32_t>&               filterBankFilterLast,
-            std::vector<float>&                 melEnergies)
-    {
-        const size_t numBanks = melEnergies.size();
-
-        if (numBanks != filterBankFilterFirst.size() ||
-            numBanks != filterBankFilterLast.size()) {
-            printf_err("unexpected filter bank lengths\n");
-            return false;
-        }
-
-        for (size_t bin = 0; bin < numBanks; ++bin) {
-            auto filterBankIter = melFilterBank[bin].begin();
-            auto end = melFilterBank[bin].end();
-            float melEnergy = FLT_MIN; /* Avoid log of zero at later stages. */
-            const uint32_t firstIndex = filterBankFilterFirst[bin];
-            const uint32_t lastIndex = std::min<int32_t>(filterBankFilterLast[bin], fftVec.size() - 1);
-
-            for (uint32_t i = firstIndex; i <= lastIndex && filterBankIter != end; ++i) {
-                melEnergy += (*filterBankIter++ * fftVec[i]);
-            }
-
-            melEnergies[bin] = melEnergy;
-        }
-
-        return true;
-    }
-
-    void AdMelSpectrogram::ConvertToLogarithmicScale(
-            std::vector<float>& melEnergies)
-    {
-        /* Container for natural logarithms of mel energies */
-        std::vector <float> vecLogEnergies(melEnergies.size(), 0.f);
-
-        /* Because we are taking natural logs, we need to multiply by log10(e).
-         * Also, for wav2letter model, we scale our log10 values by 10 */
-        constexpr float multiplier = 10.0 * /* default scalar */
-                                     0.4342944819032518; /* log10f(std::exp(1.0))*/
-
-        /* Take log of the whole vector */
-        math::MathUtils::VecLogarithmF32(melEnergies, vecLogEnergies);
-
-        /* Scale the log values. */
-        for (auto iterM = melEnergies.begin(), iterL = vecLogEnergies.begin();
-             iterM != melEnergies.end() && iterL != vecLogEnergies.end(); ++iterM, ++iterL) {
-
-            *iterM = *iterL * multiplier;
-        }
-    }
-
-    float AdMelSpectrogram::GetMelFilterBankNormaliser(
-            const float&    leftMel,
-            const float&    rightMel,
-            const bool      useHTKMethod)
-    {
-        /* Slaney normalization for mel weights. */
-        return (2.0f / (AdMelSpectrogram::InverseMelScale(rightMel, useHTKMethod) -
-                        AdMelSpectrogram::InverseMelScale(leftMel, useHTKMethod)));
-    }
-
-} /* namespace audio */
-} /* namespace app */
-} /* namespace arm */
diff --git a/source/use_case/ad/src/AdModel.cc b/source/use_case/ad/src/AdModel.cc
deleted file mode 100644
index a2ef260..0000000
--- a/source/use_case/ad/src/AdModel.cc
+++ /dev/null
@@ -1,54 +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.
- */
-#include "AdModel.hpp"
-#include "log_macros.h"
-
-const tflite::MicroOpResolver& arm::app::AdModel::GetOpResolver()
-{
-    return this->m_opResolver;
-}
-
-bool arm::app::AdModel::EnlistOperations()
-{
-    this->m_opResolver.AddAveragePool2D();
-    this->m_opResolver.AddConv2D();
-    this->m_opResolver.AddDepthwiseConv2D();
-    this->m_opResolver.AddRelu6();
-    this->m_opResolver.AddReshape();
-
-#if defined(ARM_NPU)
-    if (kTfLiteOk == this->m_opResolver.AddEthosU()) {
-        info("Added %s support to op resolver\n",
-            tflite::GetString_ETHOSU());
-    } else {
-        printf_err("Failed to add Arm NPU support to op resolver.");
-        return false;
-    }
-#endif /* ARM_NPU */
-    return true;
-}
-
-extern uint8_t* GetModelPointer();
-const uint8_t* arm::app::AdModel::ModelPointer()
-{
-    return GetModelPointer();
-}
-extern size_t GetModelLen();
-size_t arm::app::AdModel::ModelSize()
-{
-    return GetModelLen();
-}
diff --git a/source/use_case/ad/src/AdProcessing.cc b/source/use_case/ad/src/AdProcessing.cc
deleted file mode 100644
index a33131c..0000000
--- a/source/use_case/ad/src/AdProcessing.cc
+++ /dev/null
@@ -1,208 +0,0 @@
-/*
- * Copyright (c) 2022 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.
- */
-#include "AdProcessing.hpp"
-
-#include "AdModel.hpp"
-
-namespace arm {
-namespace app {
-
-AdPreProcess::AdPreProcess(TfLiteTensor* inputTensor,
-                           uint32_t melSpectrogramFrameLen,
-                           uint32_t melSpectrogramFrameStride,
-                           float adModelTrainingMean):
-       m_validInstance{false},
-       m_melSpectrogramFrameLen{melSpectrogramFrameLen},
-       m_melSpectrogramFrameStride{melSpectrogramFrameStride},
-        /**< Model is trained on features downsampled 2x */
-       m_inputResizeScale{2},
-        /**< We are choosing to move by 20 frames across the audio for each inference. */
-       m_numMelSpecVectorsInAudioStride{20},
-       m_audioDataStride{m_numMelSpecVectorsInAudioStride * melSpectrogramFrameStride},
-       m_melSpec{melSpectrogramFrameLen}
-{
-    if (!inputTensor) {
-        printf_err("Invalid input tensor provided to pre-process\n");
-        return;
-    }
-
-    TfLiteIntArray* inputShape = inputTensor->dims;
-
-    if (!inputShape) {
-        printf_err("Invalid input tensor dims\n");
-        return;
-    }
-
-    const uint32_t kNumRows = inputShape->data[AdModel::ms_inputRowsIdx];
-    const uint32_t kNumCols = inputShape->data[AdModel::ms_inputColsIdx];
-
-    /* Deduce the data length required for 1 inference from the network parameters. */
-    this->m_audioDataWindowSize = (((this->m_inputResizeScale * kNumCols) - 1) *
-                                    melSpectrogramFrameStride) +
-                                    melSpectrogramFrameLen;
-    this->m_numReusedFeatureVectors = kNumRows -
-                                      (this->m_numMelSpecVectorsInAudioStride /
-                                       this->m_inputResizeScale);
-    this->m_melSpec.Init();
-
-    /* Creating a Mel Spectrogram sliding window for the data required for 1 inference.
-     * "resizing" done here by multiplying stride by resize scale. */
-    this->m_melWindowSlider = audio::SlidingWindow<const int16_t>(
-            nullptr, /* to be populated later. */
-            this->m_audioDataWindowSize,
-            melSpectrogramFrameLen,
-            melSpectrogramFrameStride * this->m_inputResizeScale);
-
-    /* Construct feature calculation function. */
-    this->m_featureCalc = GetFeatureCalculator(this->m_melSpec, inputTensor,
-                                               this->m_numReusedFeatureVectors,
-                                               adModelTrainingMean);
-    this->m_validInstance = true;
-}
-
-bool AdPreProcess::DoPreProcess(const void* input, size_t inputSize)
-{
-    /* Check that we have a valid instance. */
-    if (!this->m_validInstance) {
-        printf_err("Invalid pre-processor instance\n");
-        return false;
-    }
-
-    /* We expect that we can traverse the size with which the MEL spectrogram
-     * sliding window was initialised with. */
-    if (!input || inputSize < this->m_audioDataWindowSize) {
-        printf_err("Invalid input provided for pre-processing\n");
-        return false;
-    }
-
-    /* We moved to the next window - set the features sliding to the new address. */
-    this->m_melWindowSlider.Reset(static_cast<const int16_t*>(input));
-
-    /* The first window does not have cache ready. */
-    const bool useCache = this->m_audioWindowIndex > 0 && this->m_numReusedFeatureVectors > 0;
-
-    /* Start calculating features inside one audio sliding window. */
-    while (this->m_melWindowSlider.HasNext()) {
-        const int16_t* melSpecWindow = this->m_melWindowSlider.Next();
-        std::vector<int16_t> melSpecAudioData = std::vector<int16_t>(
-                melSpecWindow,
-                melSpecWindow + this->m_melSpectrogramFrameLen);
-
-        /* Compute features for this window and write them to input tensor. */
-        this->m_featureCalc(melSpecAudioData,
-                            this->m_melWindowSlider.Index(),
-                            useCache,
-                            this->m_numMelSpecVectorsInAudioStride,
-                            this->m_inputResizeScale);
-    }
-
-    return true;
-}
-
-uint32_t AdPreProcess::GetAudioWindowSize()
-{
-    return this->m_audioDataWindowSize;
-}
-
-uint32_t AdPreProcess::GetAudioDataStride()
-{
-    return this->m_audioDataStride;
-}
-
-void AdPreProcess::SetAudioWindowIndex(uint32_t idx)
-{
-    this->m_audioWindowIndex = idx;
-}
-
-AdPostProcess::AdPostProcess(TfLiteTensor* outputTensor) :
-    m_outputTensor {outputTensor}
-{}
-
-bool AdPostProcess::DoPostProcess()
-{
-    switch (this->m_outputTensor->type) {
-        case kTfLiteInt8:
-            this->Dequantize<int8_t>();
-            break;
-        default:
-            printf_err("Unsupported tensor type");
-            return false;
-    }
-
-    math::MathUtils::SoftmaxF32(this->m_dequantizedOutputVec);
-    return true;
-}
-
-float AdPostProcess::GetOutputValue(uint32_t index)
-{
-    if (index < this->m_dequantizedOutputVec.size()) {
-        return this->m_dequantizedOutputVec[index];
-    }
-    printf_err("Invalid index for output\n");
-    return 0.0;
-}
-
-std::function<void (std::vector<int16_t>&, int, bool, size_t, size_t)>
-GetFeatureCalculator(audio::AdMelSpectrogram& melSpec,
-                     TfLiteTensor* inputTensor,
-                     size_t cacheSize,
-                     float trainingMean)
-{
-    std::function<void (std::vector<int16_t>&, size_t, bool, size_t, size_t)> melSpecFeatureCalc;
-
-    TfLiteQuantization quant = inputTensor->quantization;
-
-    if (kTfLiteAffineQuantization == quant.type) {
-
-        auto* quantParams = static_cast<TfLiteAffineQuantization*>(quant.params);
-        const float quantScale = quantParams->scale->data[0];
-        const int quantOffset = quantParams->zero_point->data[0];
-
-        switch (inputTensor->type) {
-            case kTfLiteInt8: {
-                melSpecFeatureCalc = FeatureCalc<int8_t>(
-                        inputTensor,
-                        cacheSize,
-                        [=, &melSpec](std::vector<int16_t>& audioDataWindow) {
-                            return melSpec.MelSpecComputeQuant<int8_t>(
-                                    audioDataWindow,
-                                    quantScale,
-                                    quantOffset,
-                                    trainingMean);
-                        }
-                );
-                break;
-            }
-            default:
-            printf_err("Tensor type %s not supported\n", TfLiteTypeGetName(inputTensor->type));
-        }
-    } else {
-        melSpecFeatureCalc = FeatureCalc<float>(
-                inputTensor,
-                cacheSize,
-                [=, &melSpec](
-                        std::vector<int16_t>& audioDataWindow) {
-                    return melSpec.ComputeMelSpec(
-                            audioDataWindow,
-                            trainingMean);
-                });
-    }
-    return melSpecFeatureCalc;
-}
-
-} /* namespace app */
-} /* namespace arm */
diff --git a/source/use_case/ad/src/MainLoop.cc b/source/use_case/ad/src/MainLoop.cc
index 140359b..e9f7b4e 100644
--- a/source/use_case/ad/src/MainLoop.cc
+++ b/source/use_case/ad/src/MainLoop.cc
@@ -18,7 +18,17 @@
 #include "AdModel.hpp"              /* Model class for running inference */
 #include "UseCaseCommonUtils.hpp"   /* Utils functions */
 #include "UseCaseHandler.hpp"       /* Handlers for different user options */
-#include "log_macros.h"
+#include "log_macros.h"             /* Logging functions */
+#include "BufAttributes.hpp"        /* Buffer attributes to be applied */
+
+namespace arm {
+    namespace app {
+        static uint8_t  tensorArena[ACTIVATION_BUF_SZ] ACTIVATION_BUF_ATTRIBUTE;
+    } /* namespace app */
+} /* namespace arm */
+
+extern uint8_t* GetModelPointer();
+extern size_t GetModelLen();
 
 enum opcodes
 {
@@ -49,12 +59,23 @@ void main_loop()
     arm::app::AdModel model;  /* Model wrapper object. */
 
     /* Load the model. */
-    if (!model.Init())
+    if (!model.Init(arm::app::tensorArena,
+                    sizeof(arm::app::tensorArena),
+                    GetModelPointer(),
+                    GetModelLen()))
     {
         printf_err("failed to initialise model\n");
         return;
     }
 
+#if !defined(ARM_NPU)
+    /* If it is not a NPU build check if the model contains a NPU operator */
+    if (model.ContainsEthosUOperator()) {
+        printf_err("No driver support for Ethos-U operator found in the model.\n");
+        return;
+    }
+#endif /* ARM_NPU */
+
     /* Instantiate application context. */
     arm::app::ApplicationContext caseContext;
 
diff --git a/source/use_case/ad/src/MelSpectrogram.cc b/source/use_case/ad/src/MelSpectrogram.cc
deleted file mode 100644
index ff0c536..0000000
--- a/source/use_case/ad/src/MelSpectrogram.cc
+++ /dev/null
@@ -1,316 +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.
- */
-#include "MelSpectrogram.hpp"
-
-#include "PlatformMath.hpp"
-#include "log_macros.h"
-
-#include <cfloat>
-#include <cinttypes>
-
-namespace arm {
-namespace app {
-namespace audio {
-
-    MelSpecParams::MelSpecParams(
-            const float samplingFreq,
-            const uint32_t numFbankBins,
-            const float melLoFreq,
-            const float melHiFreq,
-            const uint32_t frameLen,
-            const bool useHtkMethod):
-            m_samplingFreq(samplingFreq),
-            m_numFbankBins(numFbankBins),
-            m_melLoFreq(melLoFreq),
-            m_melHiFreq(melHiFreq),
-            m_frameLen(frameLen),
-
-            /* Smallest power of 2 >= frame length. */
-            m_frameLenPadded(pow(2, ceil((log(frameLen)/log(2))))),
-            m_useHtkMethod(useHtkMethod)
-    {}
-
-    std::string MelSpecParams::Str() const
-    {
-        char strC[1024];
-        snprintf(strC, sizeof(strC) - 1, "\n   \
-            \n\t Sampling frequency:         %f\
-            \n\t Number of filter banks:     %" PRIu32 "\
-            \n\t Mel frequency limit (low):  %f\
-            \n\t Mel frequency limit (high): %f\
-            \n\t Frame length:               %" PRIu32 "\
-            \n\t Padded frame length:        %" PRIu32 "\
-            \n\t Using HTK for Mel scale:    %s\n",
-            this->m_samplingFreq, this->m_numFbankBins, this->m_melLoFreq,
-            this->m_melHiFreq, this->m_frameLen,
-            this->m_frameLenPadded, this->m_useHtkMethod ? "yes" : "no");
-        return std::string{strC};
-    }
-
-    MelSpectrogram::MelSpectrogram(const MelSpecParams& params):
-            m_params(params),
-            m_filterBankInitialised(false)
-    {
-        this->m_buffer = std::vector<float>(
-                this->m_params.m_frameLenPadded, 0.0);
-        this->m_frame = std::vector<float>(
-                this->m_params.m_frameLenPadded, 0.0);
-        this->m_melEnergies = std::vector<float>(
-                this->m_params.m_numFbankBins, 0.0);
-
-        this->m_windowFunc = std::vector<float>(this->m_params.m_frameLen);
-        const auto multiplier = static_cast<float>(2 * M_PI / this->m_params.m_frameLen);
-
-        /* Create window function. */
-        for (size_t i = 0; i < this->m_params.m_frameLen; ++i) {
-            this->m_windowFunc[i] = (0.5 - (0.5 *
-                                             math::MathUtils::CosineF32(static_cast<float>(i) * multiplier)));
-        }
-
-        math::MathUtils::FftInitF32(this->m_params.m_frameLenPadded, this->m_fftInstance);
-        debug("Instantiated Mel Spectrogram object: %s\n", this->m_params.Str().c_str());
-    }
-
-    void MelSpectrogram::Init()
-    {
-        this->InitMelFilterBank();
-    }
-
-    float MelSpectrogram::MelScale(const float freq, const bool useHTKMethod)
-    {
-        if (useHTKMethod) {
-            return 1127.0f * logf (1.0f + freq / 700.0f);
-        } else {
-            /* Slaney formula for mel scale. */
-            float mel = freq / ms_freqStep;
-
-            if (freq >= ms_minLogHz) {
-                mel = ms_minLogMel + logf(freq / ms_minLogHz) / ms_logStep;
-            }
-            return mel;
-        }
-    }
-
-    float MelSpectrogram::InverseMelScale(const float melFreq, const bool useHTKMethod)
-    {
-        if (useHTKMethod) {
-            return 700.0f * (expf (melFreq / 1127.0f) - 1.0f);
-        } else {
-            /* Slaney formula for inverse mel scale. */
-            float freq = ms_freqStep * melFreq;
-
-            if (melFreq >= ms_minLogMel) {
-                freq = ms_minLogHz * expf(ms_logStep * (melFreq - ms_minLogMel));
-            }
-            return freq;
-        }
-    }
-
-    bool MelSpectrogram::ApplyMelFilterBank(
-            std::vector<float>&                 fftVec,
-            std::vector<std::vector<float>>&    melFilterBank,
-            std::vector<uint32_t>&               filterBankFilterFirst,
-            std::vector<uint32_t>&               filterBankFilterLast,
-            std::vector<float>&                 melEnergies)
-    {
-        const size_t numBanks = melEnergies.size();
-
-        if (numBanks != filterBankFilterFirst.size() ||
-            numBanks != filterBankFilterLast.size()) {
-            printf_err("unexpected filter bank lengths\n");
-            return false;
-        }
-
-        for (size_t bin = 0; bin < numBanks; ++bin) {
-            auto filterBankIter = melFilterBank[bin].begin();
-            auto end = melFilterBank[bin].end();
-            float melEnergy = FLT_MIN; /* Avoid log of zero at later stages */
-            const uint32_t firstIndex = filterBankFilterFirst[bin];
-            const uint32_t lastIndex = std::min<int32_t>(filterBankFilterLast[bin], fftVec.size() - 1);
-
-            for (uint32_t i = firstIndex; i <= lastIndex && filterBankIter != end; ++i) {
-                float energyRep = math::MathUtils::SqrtF32(fftVec[i]);
-                melEnergy += (*filterBankIter++ * energyRep);
-            }
-
-            melEnergies[bin] = melEnergy;
-        }
-
-        return true;
-    }
-
-    void MelSpectrogram::ConvertToLogarithmicScale(std::vector<float>& melEnergies)
-    {
-        for (float& melEnergy : melEnergies) {
-            melEnergy = logf(melEnergy);
-        }
-    }
-
-    void MelSpectrogram::ConvertToPowerSpectrum()
-    {
-        const uint32_t halfDim = this->m_buffer.size() / 2;
-
-        /* Handle this special case. */
-        float firstEnergy = this->m_buffer[0] * this->m_buffer[0];
-        float lastEnergy = this->m_buffer[1] * this->m_buffer[1];
-
-        math::MathUtils::ComplexMagnitudeSquaredF32(
-                this->m_buffer.data(),
-                this->m_buffer.size(),
-                this->m_buffer.data(),
-                this->m_buffer.size()/2);
-
-        this->m_buffer[0] = firstEnergy;
-        this->m_buffer[halfDim] = lastEnergy;
-    }
-
-    float MelSpectrogram::GetMelFilterBankNormaliser(
-            const float&    leftMel,
-            const float&    rightMel,
-            const bool      useHTKMethod)
-    {
-        UNUSED(leftMel);
-        UNUSED(rightMel);
-        UNUSED(useHTKMethod);
-
-        /* By default, no normalisation => return 1 */
-        return 1.f;
-    }
-
-    void MelSpectrogram::InitMelFilterBank()
-    {
-        if (!this->IsMelFilterBankInited()) {
-            this->m_melFilterBank = this->CreateMelFilterBank();
-            this->m_filterBankInitialised = true;
-        }
-    }
-
-    bool MelSpectrogram::IsMelFilterBankInited() const
-    {
-        return this->m_filterBankInitialised;
-    }
-
-    std::vector<float> MelSpectrogram::ComputeMelSpec(const std::vector<int16_t>& audioData, float trainingMean)
-    {
-        this->InitMelFilterBank();
-
-        /* TensorFlow way of normalizing .wav data to (-1, 1). */
-        constexpr float normaliser = 1.0/(1<<15);
-        for (size_t i = 0; i < this->m_params.m_frameLen; ++i) {
-            this->m_frame[i] = static_cast<float>(audioData[i]) * normaliser;
-        }
-
-        /* Apply window function to input frame. */
-        for(size_t i = 0; i < this->m_params.m_frameLen; ++i) {
-            this->m_frame[i] *= this->m_windowFunc[i];
-        }
-
-        /* Set remaining frame values to 0. */
-        std::fill(this->m_frame.begin() + this->m_params.m_frameLen,this->m_frame.end(), 0);
-
-        /* Compute FFT. */
-        math::MathUtils::FftF32(this->m_frame, this->m_buffer, this->m_fftInstance);
-
-        /* Convert to power spectrum. */
-        this->ConvertToPowerSpectrum();
-
-        /* Apply mel filterbanks. */
-        if (!this->ApplyMelFilterBank(this->m_buffer,
-                                      this->m_melFilterBank,
-                                      this->m_filterBankFilterFirst,
-                                      this->m_filterBankFilterLast,
-                                      this->m_melEnergies)) {
-            printf_err("Failed to apply MEL filter banks\n");
-        }
-
-        /* Convert to logarithmic scale */
-        this->ConvertToLogarithmicScale(this->m_melEnergies);
-
-        /* Perform mean subtraction. */
-        for (auto& energy:this->m_melEnergies) {
-            energy -= trainingMean;
-        }
-
-        return this->m_melEnergies;
-    }
-
-    std::vector<std::vector<float>> MelSpectrogram::CreateMelFilterBank()
-    {
-        size_t numFftBins = this->m_params.m_frameLenPadded / 2;
-        float fftBinWidth = static_cast<float>(this->m_params.m_samplingFreq) / this->m_params.m_frameLenPadded;
-
-        float melLowFreq = MelSpectrogram::MelScale(this->m_params.m_melLoFreq,
-                                          this->m_params.m_useHtkMethod);
-        float melHighFreq = MelSpectrogram::MelScale(this->m_params.m_melHiFreq,
-                                           this->m_params.m_useHtkMethod);
-        float melFreqDelta = (melHighFreq - melLowFreq) / (this->m_params.m_numFbankBins + 1);
-
-        std::vector<float> thisBin = std::vector<float>(numFftBins);
-        std::vector<std::vector<float>> melFilterBank(
-                this->m_params.m_numFbankBins);
-        this->m_filterBankFilterFirst =
-                std::vector<uint32_t>(this->m_params.m_numFbankBins);
-        this->m_filterBankFilterLast =
-                std::vector<uint32_t>(this->m_params.m_numFbankBins);
-
-        for (size_t bin = 0; bin < this->m_params.m_numFbankBins; bin++) {
-            float leftMel = melLowFreq + bin * melFreqDelta;
-            float centerMel = melLowFreq + (bin + 1) * melFreqDelta;
-            float rightMel = melLowFreq + (bin + 2) * melFreqDelta;
-
-            uint32_t firstIndex = 0;
-            uint32_t lastIndex = 0;
-            bool firstIndexFound = false;
-            const float normaliser = this->GetMelFilterBankNormaliser(leftMel, rightMel, this->m_params.m_useHtkMethod);
-
-            for (size_t i = 0; i < numFftBins; ++i) {
-                float freq = (fftBinWidth * i); /* Center freq of this fft bin. */
-                float mel = MelSpectrogram::MelScale(freq, this->m_params.m_useHtkMethod);
-                thisBin[i] = 0.0;
-
-                if (mel > leftMel && mel < rightMel) {
-                    float weight;
-                    if (mel <= centerMel) {
-                        weight = (mel - leftMel) / (centerMel - leftMel);
-                    } else {
-                        weight = (rightMel - mel) / (rightMel - centerMel);
-                    }
-
-                    thisBin[i] = weight * normaliser;
-                    if (!firstIndexFound) {
-                        firstIndex = i;
-                        firstIndexFound = true;
-                    }
-                    lastIndex = i;
-                }
-            }
-
-            this->m_filterBankFilterFirst[bin] = firstIndex;
-            this->m_filterBankFilterLast[bin] = lastIndex;
-
-            /* Copy the part we care about. */
-            for (uint32_t i = firstIndex; i <= lastIndex; ++i) {
-                melFilterBank[bin].push_back(thisBin[i]);
-            }
-        }
-
-        return melFilterBank;
-    }
-
-} /* namespace audio */
-} /* namespace app */
-} /* namespace arm */
diff --git a/source/use_case/ad/usecase.cmake b/source/use_case/ad/usecase.cmake
index 23b4c32..06d7681 100644
--- a/source/use_case/ad/usecase.cmake
+++ b/source/use_case/ad/usecase.cmake
@@ -15,6 +15,9 @@
 #  limitations under the License.
 #----------------------------------------------------------------------------
 
+# Append the API to use for this use case
+list(APPEND ${use_case}_API_LIST "ad")
+
 USER_OPTION(${use_case}_FILE_PATH "Directory with custom WAV input files, or path to a single input WAV file, to use in the evaluation application."
     ${CMAKE_CURRENT_SOURCE_DIR}/resources/${use_case}/samples/
     PATH_OR_FILE)