diff options
Diffstat (limited to 'source/application/api/use_case/asr/include')
7 files changed, 633 insertions, 0 deletions
diff --git a/source/application/api/use_case/asr/include/AsrClassifier.hpp b/source/application/api/use_case/asr/include/AsrClassifier.hpp new file mode 100644 index 0000000..a07a721 --- /dev/null +++ b/source/application/api/use_case/asr/include/AsrClassifier.hpp @@ -0,0 +1,63 @@ +/* + * 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 ASR_CLASSIFIER_HPP +#define ASR_CLASSIFIER_HPP + +#include "Classifier.hpp" + +namespace arm { +namespace app { + + class AsrClassifier : public Classifier { + public: + /** + * @brief Gets the top N classification results from the + * output vector. + * @param[in] outputTensor Inference output tensor from an NN model. + * @param[out] vecResults A vector of classification results + * populated by this function. + * @param[in] labels Labels vector to match classified classes + * @param[in] topNCount Number of top classifications to pick. + * @param[in] use_softmax Whether softmax scaling should be applied to model output. + * @return true if successful, false otherwise. + **/ + bool GetClassificationResults(TfLiteTensor* outputTensor, + std::vector<ClassificationResult>& vecResults, + const std::vector<std::string>& labels, + uint32_t topNCount, bool use_softmax = false) override; + + private: + /** + * @brief Utility function that gets the top 1 classification results from the + * output tensor (vector of vector). + * @param[in] tensor Inference output tensor from an NN model. + * @param[out] vecResults Vector of classification results populated by this function. + * @param[in] labels Labels vector to match classified classes. + * @param[in] scale Quantization scale. + * @param[in] zeroPoint Quantization zero point. + * @return true if successful, false otherwise. + **/ + template<typename T> + bool GetTopResults(TfLiteTensor* tensor, + std::vector<ClassificationResult>& vecResults, + const std::vector<std::string>& labels, double scale, double zeroPoint); + }; + +} /* namespace app */ +} /* namespace arm */ + +#endif /* ASR_CLASSIFIER_HPP */
\ No newline at end of file diff --git a/source/application/api/use_case/asr/include/AsrResult.hpp b/source/application/api/use_case/asr/include/AsrResult.hpp new file mode 100644 index 0000000..ed826d0 --- /dev/null +++ b/source/application/api/use_case/asr/include/AsrResult.hpp @@ -0,0 +1,63 @@ +/* + * 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 ASR_RESULT_HPP +#define ASR_RESULT_HPP + +#include "ClassificationResult.hpp" + +#include <vector> + +namespace arm { +namespace app { +namespace asr { + + using ResultVec = std::vector<arm::app::ClassificationResult>; + + /* Structure for holding ASR result. */ + class AsrResult { + + public: + ResultVec m_resultVec; /* Container for "thresholded" classification results. */ + float m_timeStamp; /* Audio timestamp for this result. */ + uint32_t m_inferenceNumber; /* Corresponding inference number. */ + float m_threshold; /* Threshold value for `m_resultVec.` */ + + AsrResult() = delete; + AsrResult(ResultVec& resultVec, + const float timestamp, + const uint32_t inferenceIdx, + const float scoreThreshold) { + + this->m_threshold = scoreThreshold; + this->m_timeStamp = timestamp; + this->m_inferenceNumber = inferenceIdx; + + this->m_resultVec = ResultVec(); + for (auto& i : resultVec) { + if (i.m_normalisedVal >= this->m_threshold) { + this->m_resultVec.emplace_back(i); + } + } + } + ~AsrResult() = default; + }; + +} /* namespace asr */ +} /* namespace app */ +} /* namespace arm */ + +#endif /* ASR_RESULT_HPP */
\ No newline at end of file diff --git a/source/application/api/use_case/asr/include/OutputDecode.hpp b/source/application/api/use_case/asr/include/OutputDecode.hpp new file mode 100644 index 0000000..9d39057 --- /dev/null +++ b/source/application/api/use_case/asr/include/OutputDecode.hpp @@ -0,0 +1,40 @@ +/* + * 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 ASR_OUTPUT_DECODE_HPP +#define ASR_OUTPUT_DECODE_HPP + +#include "AsrClassifier.hpp" + +namespace arm { +namespace app { +namespace audio { +namespace asr { + + /** + * @brief Gets the top N classification results from the + * output vector. + * @param[in] vecResults Label output from classifier. + * @return true if successful, false otherwise. + **/ + std::string DecodeOutput(const std::vector<ClassificationResult>& vecResults); + +} /* namespace asr */ +} /* namespace audio */ +} /* namespace app */ +} /* namespace arm */ + +#endif /* ASR_OUTPUT_DECODE_HPP */
\ No newline at end of file diff --git a/source/application/api/use_case/asr/include/Wav2LetterMfcc.hpp b/source/application/api/use_case/asr/include/Wav2LetterMfcc.hpp new file mode 100644 index 0000000..b5a21d3 --- /dev/null +++ b/source/application/api/use_case/asr/include/Wav2LetterMfcc.hpp @@ -0,0 +1,109 @@ +/* + * 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 ASR_WAV2LETTER_MFCC_HPP +#define ASR_WAV2LETTER_MFCC_HPP + +#include "Mfcc.hpp" + +namespace arm { +namespace app { +namespace audio { + + /* Class to provide Wav2Letter specific MFCC calculation requirements. */ + class Wav2LetterMFCC : public MFCC { + + public: + static constexpr uint32_t ms_defaultSamplingFreq = 16000; + static constexpr uint32_t ms_defaultNumFbankBins = 128; + static constexpr uint32_t ms_defaultMelLoFreq = 0; + static constexpr uint32_t ms_defaultMelHiFreq = 8000; + static constexpr bool ms_defaultUseHtkMethod = false; + + explicit Wav2LetterMFCC(const size_t numFeats, const size_t frameLen) + : MFCC(MfccParams( + ms_defaultSamplingFreq, ms_defaultNumFbankBins, + ms_defaultMelLoFreq, ms_defaultMelHiFreq, + numFeats, frameLen, ms_defaultUseHtkMethod)) + {} + + Wav2LetterMFCC() = delete; + ~Wav2LetterMFCC() = 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 + */ + 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 + **/ + void ConvertToLogarithmicScale(std::vector<float>& melEnergies) override; + + /** + * @brief Create a matrix used to calculate Discrete Cosine + * Transform. Override for the base class' default + * implementation as the first and last elements + * use a different normaliser. + * @param[in] inputLength input length of the buffer on which + * DCT will be performed + * @param[in] coefficientCount Total coefficients per input length. + * @return 1D vector with inputLength x coefficientCount elements + * populated with DCT coefficients. + */ + std::vector<float> CreateDCTMatrix(int32_t inputLength, + int32_t coefficientCount) 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 Value to use for normalising. + */ + float GetMelFilterBankNormaliser(const float& leftMel, + const float& rightMel, + bool useHTKMethod) override; + }; + +} /* namespace audio */ +} /* namespace app */ +} /* namespace arm */ + +#endif /* ASR_WAV2LETTER_MFCC_HPP */
\ No newline at end of file diff --git a/source/application/api/use_case/asr/include/Wav2LetterModel.hpp b/source/application/api/use_case/asr/include/Wav2LetterModel.hpp new file mode 100644 index 0000000..a02eed1 --- /dev/null +++ b/source/application/api/use_case/asr/include/Wav2LetterModel.hpp @@ -0,0 +1,67 @@ +/* + * 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 ASR_WAV2LETTER_MODEL_HPP +#define ASR_WAV2LETTER_MODEL_HPP + +#include "Model.hpp" + +namespace arm { +namespace app { +namespace asr { + extern const int g_FrameLength; + extern const int g_FrameStride; + extern const float g_ScoreThreshold; + extern const int g_ctxLen; +} /* namespace asr */ +} /* namespace app */ +} /* namespace arm */ + +namespace arm { +namespace app { + + class Wav2LetterModel : public Model { + + public: + /* Indices for the expected model - based on input and output tensor shapes */ + static constexpr uint32_t ms_inputRowsIdx = 1; + static constexpr uint32_t ms_inputColsIdx = 2; + static constexpr uint32_t ms_outputRowsIdx = 2; + static constexpr uint32_t ms_outputColsIdx = 3; + + /* Model specific constants. */ + static constexpr uint32_t ms_blankTokenIdx = 28; + static constexpr uint32_t ms_numMfccFeatures = 13; + + 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; + + private: + /* Maximum number of individual operations that can be enlisted. */ + static constexpr int ms_maxOpCnt = 5; + + /* A mutable op resolver instance. */ + tflite::MicroMutableOpResolver<ms_maxOpCnt> m_opResolver; + }; + +} /* namespace app */ +} /* namespace arm */ + +#endif /* ASR_WAV2LETTER_MODEL_HPP */ diff --git a/source/application/api/use_case/asr/include/Wav2LetterPostprocess.hpp b/source/application/api/use_case/asr/include/Wav2LetterPostprocess.hpp new file mode 100644 index 0000000..02738bc --- /dev/null +++ b/source/application/api/use_case/asr/include/Wav2LetterPostprocess.hpp @@ -0,0 +1,109 @@ +/* + * 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 ASR_WAV2LETTER_POSTPROCESS_HPP +#define ASR_WAV2LETTER_POSTPROCESS_HPP + +#include "TensorFlowLiteMicro.hpp" /* TensorFlow headers. */ +#include "BaseProcessing.hpp" +#include "Model.hpp" +#include "AsrClassifier.hpp" +#include "AsrResult.hpp" +#include "log_macros.h" + +namespace arm { +namespace app { + + /** + * @brief Helper class to manage tensor post-processing for "wav2letter" + * output. + */ + class AsrPostProcess : public BasePostProcess { + public: + bool m_lastIteration = false; /* Flag to set if processing the last set of data for a clip. */ + + /** + * @brief Constructor + * @param[in] outputTensor Pointer to the TFLite Micro output Tensor. + * @param[in] classifier Object used to get top N results from classification. + * @param[in] labels Vector of string labels to identify each output of the model. + * @param[in/out] result Vector of classification results to store decoded outputs. + * @param[in] outputContextLen Left/right context length for output tensor. + * @param[in] blankTokenIdx Index in the labels that the "Blank token" takes. + * @param[in] reductionAxis The axis that the logits of each time step is on. + **/ + AsrPostProcess(TfLiteTensor* outputTensor, AsrClassifier& classifier, + const std::vector<std::string>& labels, asr::ResultVec& result, + uint32_t outputContextLen, + uint32_t blankTokenIdx, uint32_t reductionAxis); + + /** + * @brief Should perform post-processing of the result of inference then + * populate ASR result data for any later use. + * @return true if successful, false otherwise. + **/ + bool DoPostProcess() override; + + /** @brief Gets the output inner length for post-processing. */ + static uint32_t GetOutputInnerLen(const TfLiteTensor*, uint32_t outputCtxLen); + + /** @brief Gets the output context length (left/right) for post-processing. */ + static uint32_t GetOutputContextLen(const Model& model, uint32_t inputCtxLen); + + /** @brief Gets the number of feature vectors to be computed. */ + static uint32_t GetNumFeatureVectors(const Model& model); + + private: + AsrClassifier& m_classifier; /* ASR Classifier object. */ + TfLiteTensor* m_outputTensor; /* Model output tensor. */ + const std::vector<std::string>& m_labels; /* ASR Labels. */ + asr::ResultVec & m_results; /* Results vector for a single inference. */ + uint32_t m_outputContextLen; /* lengths of left/right contexts for output. */ + uint32_t m_outputInnerLen; /* Length of output inner context. */ + uint32_t m_totalLen; /* Total length of the required axis. */ + uint32_t m_countIterations; /* Current number of iterations. */ + uint32_t m_blankTokenIdx; /* Index of the labels blank token. */ + uint32_t m_reductionAxisIdx; /* Axis containing output logits for a single step. */ + + /** + * @brief Checks if the tensor and axis index are valid + * inputs to the object - based on how it has been initialised. + * @return true if valid, false otherwise. + */ + bool IsInputValid(TfLiteTensor* tensor, + uint32_t axisIdx) const; + + /** + * @brief Gets the tensor data element size in bytes based + * on the tensor type. + * @return Size in bytes, 0 if not supported. + */ + static uint32_t GetTensorElementSize(TfLiteTensor* tensor); + + /** + * @brief Erases sections from the data assuming row-wise + * arrangement along the context axis. + * @return true if successful, false otherwise. + */ + bool EraseSectionsRowWise(uint8_t* ptrData, + uint32_t strideSzBytes, + bool lastIteration); + }; + +} /* namespace app */ +} /* namespace arm */ + +#endif /* ASR_WAV2LETTER_POSTPROCESS_HPP */
\ No newline at end of file diff --git a/source/application/api/use_case/asr/include/Wav2LetterPreprocess.hpp b/source/application/api/use_case/asr/include/Wav2LetterPreprocess.hpp new file mode 100644 index 0000000..9943946 --- /dev/null +++ b/source/application/api/use_case/asr/include/Wav2LetterPreprocess.hpp @@ -0,0 +1,182 @@ +/* + * 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 ASR_WAV2LETTER_PREPROCESS_HPP +#define ASR_WAV2LETTER_PREPROCESS_HPP + +#include "TensorFlowLiteMicro.hpp" +#include "Wav2LetterMfcc.hpp" +#include "AudioUtils.hpp" +#include "DataStructures.hpp" +#include "BaseProcessing.hpp" +#include "log_macros.h" + +namespace arm { +namespace app { + + /* Class to facilitate pre-processing calculation for Wav2Letter model + * for ASR. */ + using AudioWindow = audio::SlidingWindow<const int16_t>; + + class AsrPreProcess : public BasePreProcess { + public: + /** + * @brief Constructor. + * @param[in] inputTensor Pointer to the TFLite Micro input Tensor. + * @param[in] numMfccFeatures Number of MFCC features per window. + * @param[in] numFeatureFrames Number of MFCC vectors that need to be calculated + * for an inference. + * @param[in] mfccWindowLen Number of audio elements to calculate MFCC features per window. + * @param[in] mfccWindowStride Stride (in number of elements) for moving the MFCC window. + */ + AsrPreProcess(TfLiteTensor* inputTensor, + uint32_t numMfccFeatures, + uint32_t numFeatureFrames, + uint32_t mfccWindowLen, + uint32_t mfccWindowStride); + + /** + * @brief Calculates the features required from audio data. This + * includes MFCC, first and second order deltas, + * normalisation and finally, quantisation. The tensor is + * populated with features from a given window placed along + * in a single row. + * @param[in] audioData Pointer to the first element of audio data. + * @param[in] audioDataLen Number of elements in the audio data. + * @return true if successful, false in case of error. + */ + bool DoPreProcess(const void* audioData, size_t audioDataLen) override; + + protected: + /** + * @brief Computes the first and second order deltas for the + * MFCC buffers - they are assumed to be populated. + * + * @param[in] mfcc MFCC buffers. + * @param[out] delta1 Result of the first diff computation. + * @param[out] delta2 Result of the second diff computation. + * @return true if successful, false otherwise. + */ + static bool ComputeDeltas(Array2d<float>& mfcc, + Array2d<float>& delta1, + Array2d<float>& delta2); + + /** + * @brief Given a 2D vector of floats, rescale it to have mean of 0 and + * standard deviation of 1. + * @param[in,out] vec Vector of vector of floats. + */ + static void StandardizeVecF32(Array2d<float>& vec); + + /** + * @brief Standardizes all the MFCC and delta buffers to have mean 0 and std. dev 1. + */ + void Standarize(); + + /** + * @brief Given the quantisation and data type limits, computes + * the quantised values of a floating point input data. + * @param[in] elem Element to be quantised. + * @param[in] quantScale Scale. + * @param[in] quantOffset Offset. + * @param[in] minVal Numerical limit - minimum. + * @param[in] maxVal Numerical limit - maximum. + * @return Floating point quantised value. + */ + static float GetQuantElem( + float elem, + float quantScale, + int quantOffset, + float minVal, + float maxVal); + + /** + * @brief Quantises the MFCC and delta buffers, and places them + * in the output buffer. While doing so, it transposes + * the data. Reason: Buffers in this class are arranged + * for "time" axis to be row major. Primary reason for + * this being the convolution speed up (as we can use + * contiguous memory). The output, however, requires the + * time axis to be in column major arrangement. + * @param[in] outputBuf Pointer to the output buffer. + * @param[in] outputBufSz Output buffer's size. + * @param[in] quantScale Quantisation scale. + * @param[in] quantOffset Quantisation offset. + */ + template <typename T> + bool Quantise( + T* outputBuf, + const uint32_t outputBufSz, + const float quantScale, + const int quantOffset) + { + /* Check the output size will fit everything. */ + if (outputBufSz < (this->m_mfccBuf.size(0) * 3 * sizeof(T))) { + printf_err("Tensor size too small for features\n"); + return false; + } + + /* Populate. */ + T* outputBufMfcc = outputBuf; + T* outputBufD1 = outputBuf + this->m_numMfccFeats; + T* outputBufD2 = outputBufD1 + this->m_numMfccFeats; + const uint32_t ptrIncr = this->m_numMfccFeats * 2; /* (3 vectors - 1 vector) */ + + const float minVal = std::numeric_limits<T>::min(); + const float maxVal = std::numeric_limits<T>::max(); + + /* Need to transpose while copying and concatenating the tensor. */ + for (uint32_t j = 0; j < this->m_numFeatureFrames; ++j) { + for (uint32_t i = 0; i < this->m_numMfccFeats; ++i) { + *outputBufMfcc++ = static_cast<T>(AsrPreProcess::GetQuantElem( + this->m_mfccBuf(i, j), quantScale, + quantOffset, minVal, maxVal)); + *outputBufD1++ = static_cast<T>(AsrPreProcess::GetQuantElem( + this->m_delta1Buf(i, j), quantScale, + quantOffset, minVal, maxVal)); + *outputBufD2++ = static_cast<T>(AsrPreProcess::GetQuantElem( + this->m_delta2Buf(i, j), quantScale, + quantOffset, minVal, maxVal)); + } + outputBufMfcc += ptrIncr; + outputBufD1 += ptrIncr; + outputBufD2 += ptrIncr; + } + + return true; + } + + private: + audio::Wav2LetterMFCC m_mfcc; /* MFCC instance. */ + TfLiteTensor* m_inputTensor; /* Model input tensor. */ + + /* Actual buffers to be populated. */ + Array2d<float> m_mfccBuf; /* Contiguous buffer 1D: MFCC */ + Array2d<float> m_delta1Buf; /* Contiguous buffer 1D: Delta 1 */ + Array2d<float> m_delta2Buf; /* Contiguous buffer 1D: Delta 2 */ + + uint32_t m_mfccWindowLen; /* Window length for MFCC. */ + uint32_t m_mfccWindowStride; /* Window stride len for MFCC. */ + uint32_t m_numMfccFeats; /* Number of MFCC features per window. */ + uint32_t m_numFeatureFrames; /* How many sets of m_numMfccFeats. */ + AudioWindow m_mfccSlidingWindow; /* Sliding window to calculate MFCCs. */ + + }; + +} /* namespace app */ +} /* namespace arm */ + +#endif /* ASR_WAV2LETTER_PREPROCESS_HPP */
\ No newline at end of file |