MLECO-2079 Adding the C++ KWS example
Signed-off-by: Eanna O Cathain <eanna.ocathain@arm.com>
Change-Id: I81899bbfaada32f478c2e2fc6441eabb94d8d0fc
diff --git a/samples/SpeechRecognition/src/SpeechRecognitionPipeline.cpp b/samples/SpeechRecognition/src/SpeechRecognitionPipeline.cpp
index 1b822d6..8b7dd11 100644
--- a/samples/SpeechRecognition/src/SpeechRecognitionPipeline.cpp
+++ b/samples/SpeechRecognition/src/SpeechRecognitionPipeline.cpp
@@ -6,21 +6,86 @@
#include "SpeechRecognitionPipeline.hpp"
#include "ArmnnNetworkExecutor.hpp"
-namespace asr
+namespace asr
{
+
ASRPipeline::ASRPipeline(std::unique_ptr<common::ArmnnNetworkExecutor<int8_t>> executor,
- std::unique_ptr<Decoder> decoder
- ) :
+ std::unique_ptr<Decoder> decoder, std::unique_ptr<Wav2LetterPreprocessor> preProcessor) :
m_executor(std::move(executor)),
- m_decoder(std::move(decoder)){}
+ m_decoder(std::move(decoder)), m_preProcessor(std::move(preProcessor)) {}
-IPipelinePtr CreatePipeline(common::PipelineOptions& config, std::map<int, std::string>& labels)
+int ASRPipeline::getInputSamplesSize()
{
- auto executor = std::make_unique<common::ArmnnNetworkExecutor<int8_t>>(config.m_ModelFilePath, config.m_backends);
+ return this->m_preProcessor->m_windowLen +
+ ((this->m_preProcessor->m_mfcc->m_params.m_numMfccVectors - 1) * this->m_preProcessor->m_windowStride);
+}
- auto decoder = std::make_unique<asr::Decoder>(labels);
+int ASRPipeline::getSlidingWindowOffset()
+{
+ // Hardcoded for now until refactor
+ return ASRPipeline::SLIDING_WINDOW_OFFSET;
+}
- return std::make_unique<asr::ASRPipeline>(std::move(executor), std::move(decoder));
+std::vector<int8_t> ASRPipeline::PreProcessing(std::vector<float>& audio)
+{
+ int audioDataToPreProcess = m_preProcessor->m_windowLen +
+ ((m_preProcessor->m_mfcc->m_params.m_numMfccVectors - 1) *
+ m_preProcessor->m_windowStride);
+ int outputBufferSize = m_preProcessor->m_mfcc->m_params.m_numMfccVectors
+ * m_preProcessor->m_mfcc->m_params.m_numMfccFeatures * 3;
+ std::vector<int8_t> outputBuffer(outputBufferSize);
+ m_preProcessor->Invoke(audio.data(), audioDataToPreProcess, outputBuffer, m_executor->GetQuantizationOffset(),
+ m_executor->GetQuantizationScale());
+ return outputBuffer;
+}
+
+IPipelinePtr CreatePipeline(common::PipelineOptions& config, std::map<int, std::string>& labels)
+{
+ if (config.m_ModelName == "Wav2Letter")
+ {
+ // Wav2Letter ASR SETTINGS
+ int SAMP_FREQ = 16000;
+ int FRAME_LEN_MS = 32;
+ int FRAME_LEN_SAMPLES = SAMP_FREQ * FRAME_LEN_MS * 0.001;
+ int NUM_MFCC_FEATS = 13;
+ int MFCC_WINDOW_LEN = 512;
+ int MFCC_WINDOW_STRIDE = 160;
+ const int NUM_MFCC_VECTORS = 296;
+ int SAMPLES_PER_INFERENCE = MFCC_WINDOW_LEN + ((NUM_MFCC_VECTORS - 1) * MFCC_WINDOW_STRIDE);
+ int MEL_LO_FREQ = 0;
+ int MEL_HI_FREQ = 8000;
+ int NUM_FBANK_BIN = 128;
+ int INPUT_WINDOW_LEFT_CONTEXT = 98;
+ int INPUT_WINDOW_RIGHT_CONTEXT = 98;
+ int INPUT_WINDOW_INNER_CONTEXT = NUM_MFCC_VECTORS -
+ (INPUT_WINDOW_LEFT_CONTEXT + INPUT_WINDOW_RIGHT_CONTEXT);
+ int SLIDING_WINDOW_OFFSET = INPUT_WINDOW_INNER_CONTEXT * MFCC_WINDOW_STRIDE;
+
+
+ MfccParams mfccParams(SAMP_FREQ, NUM_FBANK_BIN,
+ MEL_LO_FREQ, MEL_HI_FREQ, NUM_MFCC_FEATS, FRAME_LEN_SAMPLES, false, NUM_MFCC_VECTORS);
+
+ std::unique_ptr<Wav2LetterMFCC> mfccInst = std::make_unique<Wav2LetterMFCC>(mfccParams);
+
+ auto executor = std::make_unique<common::ArmnnNetworkExecutor<int8_t>>(config.m_ModelFilePath,
+ config.m_backends);
+
+ auto decoder = std::make_unique<asr::Decoder>(labels);
+
+ auto preprocessor = std::make_unique<Wav2LetterPreprocessor>(MFCC_WINDOW_LEN, MFCC_WINDOW_STRIDE,
+ std::move(mfccInst));
+
+ auto ptr = std::make_unique<asr::ASRPipeline>(
+ std::move(executor), std::move(decoder), std::move(preprocessor));
+
+ ptr->SLIDING_WINDOW_OFFSET = SLIDING_WINDOW_OFFSET;
+
+ return ptr;
+ }
+ else
+ {
+ throw std::invalid_argument("Unknown Model name: " + config.m_ModelName + " .");
+ }
}
}// namespace asr
\ No newline at end of file