MLECO-3173: Add AD, KWS_ASR and Noise reduction use case API's

Signed-off-by: Richard Burton <richard.burton@arm.com>

Change-Id: I36f61ce74bf17f7b327cdae9704a22ca54144f37

2 files changed, 123 insertions, 6 deletions

diff --git a/source/use_case/noise_reduction/include/RNNoiseProcess.hpp b/source/use_case/noise_reduction/include/RNNoiseFeatureProcessor.hpp
index c188e42..cbf0e4e 100644
--- a/source/use_case/noise_reduction/include/RNNoiseProcess.hpp
+++ b/source/use_case/noise_reduction/include/RNNoiseFeatureProcessor.hpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * 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");
@@ -14,6 +14,9 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+#ifndef RNNOISE_FEATURE_PROCESSOR_HPP
+#define RNNOISE_FEATURE_PROCESSOR_HPP
+
 #include "PlatformMath.hpp"
 #include <cstdint>
 #include <vector>
@@ -47,11 +50,11 @@ namespace rnn {
      *          - https://jmvalin.ca/demo/rnnoise/
      *          - https://arxiv.org/abs/1709.08243
      **/
-    class RNNoiseProcess {
+    class RNNoiseFeatureProcessor {
     /* Public interface */
     public:
-        RNNoiseProcess();
-        ~RNNoiseProcess() = default;
+        RNNoiseFeatureProcessor();
+        ~RNNoiseFeatureProcessor() = default;
 
         /**
          * @brief        Calculates the features from a given audio buffer ready to be sent to RNNoise model.
@@ -328,10 +331,11 @@ namespace rnn {
         const std::array <uint32_t, NB_BANDS> m_eband5ms {
             0,  1,  2,  3,  4,  5,  6,  7,  8, 10,  12,
             14, 16, 20, 24, 28, 34, 40, 48, 60, 78, 100};
-
     };
 
 
 } /* namespace rnn */
-} /* namspace app */
+} /* namespace app */
 } /* namespace arm */
+
+#endif /* RNNOISE_FEATURE_PROCESSOR_HPP */
diff --git a/source/use_case/noise_reduction/include/RNNoiseProcessing.hpp b/source/use_case/noise_reduction/include/RNNoiseProcessing.hpp
new file mode 100644
index 0000000..15e62d9
--- /dev/null
+++ b/source/use_case/noise_reduction/include/RNNoiseProcessing.hpp
@@ -0,0 +1,113 @@
+/*
+ * 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 RNNOISE_PROCESSING_HPP
+#define RNNOISE_PROCESSING_HPP
+
+#include "BaseProcessing.hpp"
+#include "Model.hpp"
+#include "RNNoiseFeatureProcessor.hpp"
+
+namespace arm {
+namespace app {
+
+    /**
+     * @brief   Pre-processing class for Noise Reduction use case.
+     *          Implements methods declared by BasePreProcess and anything else needed
+     *          to populate input tensors ready for inference.
+     */
+    class RNNoisePreProcess : public BasePreProcess {
+
+    public:
+        /**
+         * @brief           Constructor
+         * @param[in]       inputTensor        Pointer to the TFLite Micro input Tensor.
+         * @param[in/out]   featureProcessor   RNNoise specific feature extractor object.
+         * @param[in/out]   frameFeatures      RNNoise specific features shared between pre & post-processing.
+         *
+         **/
+        explicit RNNoisePreProcess(TfLiteTensor* inputTensor,
+                                   std::shared_ptr<rnn::RNNoiseFeatureProcessor> featureProcessor,
+                                   std::shared_ptr<rnn::FrameFeatures> frameFeatures);
+
+        /**
+         * @brief       Should perform pre-processing of 'raw' input audio data and load it into
+         *              TFLite Micro input tensors ready for inference
+         * @param[in]   input      Pointer to the data that pre-processing will work on.
+         * @param[in]   inputSize  Size of the input data.
+         * @return      true if successful, false otherwise.
+         **/
+        bool DoPreProcess(const void* input, size_t inputSize) override;
+
+    private:
+        TfLiteTensor* m_inputTensor;                        /* Model input tensor. */
+        std::shared_ptr<rnn::RNNoiseFeatureProcessor> m_featureProcessor;   /* RNNoise feature processor shared between pre & post-processing. */
+        std::shared_ptr<rnn::FrameFeatures> m_frameFeatures;                /* RNNoise features shared between pre & post-processing. */
+        rnn::vec1D32F m_audioFrame;                         /* Audio frame cast to FP32 */
+
+        /**
+         * @brief            Quantize the given features and populate the input Tensor.
+         * @param[in]        inputFeatures   Vector of floating point features to quantize.
+         * @param[in]        quantScale      Quantization scale for the inputTensor.
+         * @param[in]        quantOffset     Quantization offset for the inputTensor.
+         * @param[in,out]    inputTensor     TFLite micro tensor to populate.
+         **/
+        static void QuantizeAndPopulateInput(rnn::vec1D32F& inputFeatures,
+                float quantScale, int quantOffset,
+                TfLiteTensor* inputTensor);
+    };
+
+    /**
+     * @brief   Post-processing class for Noise Reduction use case.
+     *          Implements methods declared by BasePostProcess and anything else needed
+     *          to populate result vector.
+     */
+    class RNNoisePostProcess : public BasePostProcess {
+
+    public:
+        /**
+         * @brief           Constructor
+         * @param[in]       outputTensor         Pointer to the TFLite Micro output Tensor.
+         * @param[out]      denoisedAudioFrame   Vector to store the final denoised audio frame.
+         * @param[in/out]   featureProcessor     RNNoise specific feature extractor object.
+         * @param[in/out]   frameFeatures        RNNoise specific features shared between pre & post-processing.
+         **/
+        RNNoisePostProcess(TfLiteTensor* outputTensor,
+                           std::vector<int16_t>& denoisedAudioFrame,
+                           std::shared_ptr<rnn::RNNoiseFeatureProcessor> featureProcessor,
+                           std::shared_ptr<rnn::FrameFeatures> frameFeatures);
+
+        /**
+         * @brief       Should perform post-processing of the result of inference then
+         *              populate result data for any later use.
+         * @return      true if successful, false otherwise.
+         **/
+        bool DoPostProcess() override;
+
+    private:
+        TfLiteTensor* m_outputTensor;                       /* Model output tensor. */
+        std::vector<int16_t>& m_denoisedAudioFrame;         /* Vector to store the final denoised frame. */
+        rnn::vec1D32F m_denoisedAudioFrameFloat;            /* Internal vector to store the final denoised frame (FP32). */
+        std::shared_ptr<rnn::RNNoiseFeatureProcessor> m_featureProcessor;   /* RNNoise feature processor shared between pre & post-processing. */
+        std::shared_ptr<rnn::FrameFeatures> m_frameFeatures;                /* RNNoise features shared between pre & post-processing. */
+        std::vector<float> m_modelOutputFloat;              /* Internal vector to store de-quantized model output. */
+
+    };
+
+} /* namespace app */
+} /* namespace arm */
+
+#endif /* RNNOISE_PROCESSING_HPP */
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