MLECO-3077: Add ASR use case API
* Minor adjustments to doc strings in KWS
* Remove unused score threshold in KWS
Signed-off-by: Richard Burton <richard.burton@arm.com>
Change-Id: Ie1c5bf6f7bdbebb853b6a10cb7ba1c4a1d9a76c9
diff --git a/source/use_case/kws/include/KwsProcessing.hpp b/source/use_case/kws/include/KwsProcessing.hpp
index abf20ab..ddf38c1 100644
--- a/source/use_case/kws/include/KwsProcessing.hpp
+++ b/source/use_case/kws/include/KwsProcessing.hpp
@@ -38,7 +38,7 @@
public:
/**
* @brief Constructor
- * @param[in] model Pointer to the the KWS Model object.
+ * @param[in] model Pointer to the KWS Model object.
* @param[in] numFeatures How many MFCC features to use.
* @param[in] mfccFrameLength Number of audio samples used to calculate one set of MFCC values when
* sliding a window through the audio sample.
@@ -107,24 +107,21 @@
std::vector<ClassificationResult>& m_results;
public:
- const float m_scoreThreshold;
/**
- * @brief Constructor
- * @param[in] classifier Classifier object used to get top N results from classification.
- * @param[in] model Pointer to the the Image classification Model object.
- * @param[in] labels Vector of string labels to identify each output of the model.
- * @param[in] results Vector of classification results to store decoded outputs.
- * @param[in] scoreThreshold Predicted model score must be larger than this value to be accepted.
+ * @brief Constructor
+ * @param[in] classifier Classifier object used to get top N results from classification.
+ * @param[in] model Pointer to the KWS Model object.
+ * @param[in] labels Vector of string labels to identify each output of the model.
+ * @param[in/out] results Vector of classification results to store decoded outputs.
**/
KWSPostProcess(Classifier& classifier, Model* model,
const std::vector<std::string>& labels,
- std::vector<ClassificationResult>& results,
- float scoreThreshold);
+ std::vector<ClassificationResult>& results);
/**
- * @brief Should perform post-processing of the result of inference then populate
- * populate KWS result data for any later use.
- * @return true if successful, false otherwise.
+ * @brief Should perform post-processing of the result of inference then
+ * populate KWS result data for any later use.
+ * @return true if successful, false otherwise.
**/
bool DoPostProcess() override;
};
diff --git a/source/use_case/kws/src/KwsProcessing.cc b/source/use_case/kws/src/KwsProcessing.cc
index b6b230c..14f9fce 100644
--- a/source/use_case/kws/src/KwsProcessing.cc
+++ b/source/use_case/kws/src/KwsProcessing.cc
@@ -197,11 +197,10 @@
KWSPostProcess::KWSPostProcess(Classifier& classifier, Model* model,
const std::vector<std::string>& labels,
- std::vector<ClassificationResult>& results, float scoreThreshold)
+ std::vector<ClassificationResult>& results)
:m_kwsClassifier{classifier},
m_labels{labels},
- m_results{results},
- m_scoreThreshold{scoreThreshold}
+ m_results{results}
{
if (!model->IsInited()) {
printf_err("Model is not initialised!.\n");
diff --git a/source/use_case/kws/src/UseCaseHandler.cc b/source/use_case/kws/src/UseCaseHandler.cc
index 350d34b..e73a2c3 100644
--- a/source/use_case/kws/src/UseCaseHandler.cc
+++ b/source/use_case/kws/src/UseCaseHandler.cc
@@ -93,7 +93,7 @@
std::vector<ClassificationResult> singleInfResult;
KWSPostProcess postprocess = KWSPostProcess(ctx.Get<KwsClassifier &>("classifier"), &model,
ctx.Get<std::vector<std::string>&>("labels"),
- singleInfResult, scoreThreshold);
+ singleInfResult);
UseCaseRunner runner = UseCaseRunner(&preprocess, &postprocess, &model);
@@ -146,7 +146,7 @@
/* Add results from this window to our final results vector. */
finalResults.emplace_back(kws::KwsResult(singleInfResult,
audioDataSlider.Index() * secondsPerSample * preprocess.m_audioDataStride,
- audioDataSlider.Index(), postprocess.m_scoreThreshold));
+ audioDataSlider.Index(), scoreThreshold));
#if VERIFY_TEST_OUTPUT
TfLiteTensor* outputTensor = model.GetOutputTensor(0);