/* * SPDX-FileCopyrightText: Copyright 2021-2023 Arm Limited and/or its affiliates * 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; 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& mfcc, Array2d& delta1, Array2d& 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& 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 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.dimSize(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::min(); const float maxVal = std::numeric_limits::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(AsrPreProcess::GetQuantElem( this->m_mfccBuf(i, j), quantScale, quantOffset, minVal, maxVal)); *outputBufD1++ = static_cast(AsrPreProcess::GetQuantElem( this->m_delta1Buf(i, j), quantScale, quantOffset, minVal, maxVal)); *outputBufD2++ = static_cast(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 m_mfccBuf; /* Contiguous buffer 1D: MFCC */ Array2d m_delta1Buf; /* Contiguous buffer 1D: Delta 1 */ Array2d 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 */