1 files changed, 28 insertions, 31 deletions

diff --git a/samples/SpeechRecognition/include/SpeechRecognitionPipeline.hpp b/samples/SpeechRecognition/include/SpeechRecognitionPipeline.hpp
index 47ce30416f..bc3fbfe151 100644
--- a/samples/SpeechRecognition/include/SpeechRecognitionPipeline.hpp
+++ b/samples/SpeechRecognition/include/SpeechRecognitionPipeline.hpp
@@ -8,16 +8,16 @@
 #include "ArmnnNetworkExecutor.hpp"
 #include "Decoder.hpp"
 #include "MFCC.hpp"
-#include "Preprocess.hpp"
+#include "Wav2LetterPreprocessor.hpp"
 
-namespace asr
+namespace asr 
 {
 /**
  * Generic Speech Recognition pipeline with 3 steps: data pre-processing, inference execution and inference
  * result post-processing.
  *
  */
-class ASRPipeline
+class ASRPipeline 
 {
 public:
 
@@ -27,7 +27,7 @@ public:
      * @param decoder - unique pointer to inference results decoder
      */
     ASRPipeline(std::unique_ptr<common::ArmnnNetworkExecutor<int8_t>> executor,
-                std::unique_ptr<Decoder> decoder);
+                std::unique_ptr<Decoder> decoder, std::unique_ptr<Wav2LetterPreprocessor> preprocessor);
 
     /**
      * @brief Standard audio pre-processing implementation.
@@ -36,20 +36,16 @@ public:
      * extracting the MFCC features.
 
      * @param[in] audio - the raw audio data
-     * @param[out] preprocessor - the preprocessor object, which handles the data prepreration
+     * @param[out] preprocessor - the preprocessor object, which handles the data preparation
      */
-    template<typename Tin,typename Tout>
-    std::vector<Tout> PreProcessing(std::vector<Tin>& audio, Preprocess& preprocessor)
-    {
-        int audioDataToPreProcess = preprocessor._m_windowLen +
-                ((preprocessor._m_mfcc._m_params.m_numMfccVectors -1) *preprocessor._m_windowStride);
-        int outputBufferSize = preprocessor._m_mfcc._m_params.m_numMfccVectors
-                * preprocessor._m_mfcc._m_params.m_numMfccFeatures * 3;
-        std::vector<Tout> outputBuffer(outputBufferSize);
-        preprocessor.Invoke(audio.data(), audioDataToPreProcess, outputBuffer, m_executor->GetQuantizationOffset(),
-                            m_executor->GetQuantizationScale());
-        return outputBuffer;
-    }
+    std::vector<int8_t> PreProcessing(std::vector<float>& audio);
+
+    int getInputSamplesSize();
+    int getSlidingWindowOffset();
+
+    // Exposing hardcoded constant as it can only be derived from model knowledge and not from model itself
+    // Will need to be refactored so that hard coded values are not defined outside of model settings
+    int SLIDING_WINDOW_OFFSET;
 
     /**
      * @brief Executes inference
@@ -60,9 +56,9 @@ public:
      * @param[out] result - raw inference results.
      */
     template<typename T>
-    void Inference(const std::vector<T>& preprocessedData, common::InferenceResults<int8_t>& result)
+    void Inference(const std::vector<T>& preprocessedData, common::InferenceResults<int8_t>& result) 
     {
-        size_t data_bytes = sizeof(std::vector<T>) + (sizeof(T) * preprocessedData.size());
+        size_t data_bytes = sizeof(T) * preprocessedData.size();
         m_executor->Run(preprocessedData.data(), data_bytes, result);
     }
 
@@ -78,9 +74,9 @@ public:
      */
     template<typename T>
     void PostProcessing(common::InferenceResults<int8_t>& inferenceResult,
-                                     bool& isFirstWindow,
-                                     bool isLastWindow,
-                                     std::string currentRContext)
+                        bool& isFirstWindow,
+                        bool isLastWindow,
+                        std::string currentRContext) 
     {
         int rowLength = 29;
         int middleContextStart = 49;
@@ -92,17 +88,17 @@ public:
         std::vector<T> contextToProcess;
 
         // If isFirstWindow we keep the left context of the output
-        if(isFirstWindow)
+        if (isFirstWindow) 
         {
             std::vector<T> chunk(&inferenceResult[0][leftContextStart],
-                    &inferenceResult[0][middleContextEnd * rowLength]);
+                                 &inferenceResult[0][middleContextEnd * rowLength]);
             contextToProcess = chunk;
         }
-        // Else we only keep the middle context of the output
-        else
+        else 
         {
+            // Else we only keep the middle context of the output
             std::vector<T> chunk(&inferenceResult[0][middleContextStart * rowLength],
-                    &inferenceResult[0][middleContextEnd * rowLength]);
+                                 &inferenceResult[0][middleContextEnd * rowLength]);
             contextToProcess = chunk;
         }
         std::string output = this->m_decoder->DecodeOutput<T>(contextToProcess);
@@ -110,10 +106,10 @@ public:
         std::cout << output << std::flush;
 
         // If this is the last window, we print the right context of the output
-        if(isLastWindow)
+        if (isLastWindow) 
         {
-            std::vector<T> rContext(&inferenceResult[0][rightContextStart*rowLength],
-                    &inferenceResult[0][rightContextEnd * rowLength]);
+            std::vector<T> rContext(&inferenceResult[0][rightContextStart * rowLength],
+                                    &inferenceResult[0][rightContextEnd * rowLength]);
             currentRContext = this->m_decoder->DecodeOutput(rContext);
             std::cout << currentRContext << std::endl;
         }
@@ -122,6 +118,7 @@ public:
 protected:
     std::unique_ptr<common::ArmnnNetworkExecutor<int8_t>> m_executor;
     std::unique_ptr<Decoder> m_decoder;
+    std::unique_ptr<Wav2LetterPreprocessor> m_preProcessor;
 };
 
 using IPipelinePtr = std::unique_ptr<asr::ASRPipeline>;
@@ -136,4 +133,4 @@ using IPipelinePtr = std::unique_ptr<asr::ASRPipeline>;
  */
 IPipelinePtr CreatePipeline(common::PipelineOptions& config, std::map<int, std::string>& labels);
 
-}// namespace asr
\ No newline at end of file
+} // namespace asr
\ No newline at end of file