/github/workspace/src/TransformFunctions/plp_mfcc_f32.c

Functions

	Name
void	plp_mfcc_f32(const plp_fft_instance_f32 * SFFT, const plp_fft_instance_f32 * SDCT, const Complex_type_f32 * pShift, const plp_triangular_filter_f32 * filterBank, const float32_t * window, const uint8_t * orthoNorm, const float32_t restrict pSrc, float32_t restrict pDst) MFCC on real input data.

Functions Documentation

function plp_mfcc_f32

void plp_mfcc_f32(
    const plp_fft_instance_f32 * SFFT,
    const plp_fft_instance_f32 * SDCT,
    const Complex_type_f32 * pShift,
    const plp_triangular_filter_f32 * filterBank,
    const float32_t * window,
    const uint8_t * orthoNorm,
    const float32_t *__restrict__ pSrc,
    float32_t *__restrict__ pDst
)

MFCC on real input data.

Parameters:

• SFFT points to an instance of the floating-point FFT structure for the initial FFT (with FFTLength = n_fft). bitReverseFlag should be on.
• SDCT points to an instance of the floating-point FFT structure for the DCT (with FFTLength = n_mels). bitReverseFlag should be on.
• pShift points to twiddle coefficient table with FFTLength = 4*n_mels. Only first quarter necessary.
• filterBank points to plp_triangular_filter_f32 instance with nFilters = n_mels.
• window vector to use for windowing
• orthoNorm whether to use dct orthonormalisation or not
• pSrc points to the input buffer (real data, size n_fft)
• pDst points to the output buffer of length at least 3*n_fft. pSrc and pDst must not overlap, the calculation can not be done in place. MFCCs are returned in the first n_mels spots.

Return: none

Source code

/* ----------------------------------------------------------------------
 * Project:      PULP DSP Library
 * Title:        plp_mfcc_f32.c
 * Description:  Floating-point MFCC on real input data
 *
 * $Date:        05. July 2021
 * $Revision:    V0
 *
 * Target Processor: PULP cores with "F" support (wolfe, vega)
 * -------------------------------------------------------------------- */
/*
 * Copyright (C) 2021 ETH Zurich and University of Bologna. All rights reserved.
 *
 * Author: Aron Szakacs, ETH Zurich
 *
 * 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
 *
 * 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.
 */

#include "plp_math.h"

void plp_mfcc_f32(const plp_fft_instance_f32 *SFFT,
                  const plp_fft_instance_f32 *SDCT,
          const Complex_type_f32 *pShift,
          const plp_triangular_filter_f32 *filterBank,
          const float32_t *window,
          const uint8_t *orthoNorm,
                  const float32_t *__restrict__ pSrc,
                  float32_t *__restrict__ pDst) {


    // Step 0: Windowing. Stored in buffer space of pDst.
    uint32_t n_fft = SFFT->FFTLength;
    float32_t *fft_in = pDst + 2*n_fft;
    plp_mult_f32(window, pSrc, fft_in, n_fft);


    // Step 1: FFT
    plp_rfft_f32(SFFT, fft_in, pDst);


    // Step 2: ||.||^2 of each RFFT point / Take squared magnitude.
    // Stores result in free buffer space of pDst, right behind
    // the RFFT's (n_fft+2)-long output. 
    float32_t *fft_mag = pDst + n_fft+2;
    plp_cmplx_mag_squared_f32(pDst, fft_mag, n_fft/2 + 1);


    // Step 3: Apply triangular filter bank.
    // results are stored in the beginning of pDst.
    float32_t *fb_out = pDst;
    uint16_t n_mels = filterBank->nFilters;
    float32_t *filter_start = (float32_t*)filterBank->V;
    for (int i=0;i<n_mels;i++){
        uint16_t current_length = filterBank->filterLength[i];
        plp_dot_prod_f32(
                          fft_mag+filterBank->firstValue[i], 
                          filter_start,
                          current_length, 
                          fb_out+i);
        filter_start += current_length;
    }


    // Step 4: Take the log of the computed mel scale. 
    // the offset is copied from pytorch
    plp_offset_f32(fb_out, 1e-6f, fb_out, n_mels);
    float32_t *mel_logs = fb_out;
    for (int i=0;i<n_mels;i++){
            float32_t log_i = log(fb_out[i]);
            mel_logs[i] = log_i;
    }


    // Step 5: DCT of log mels
    // corresponds to using pytorch MFCC with norm = None
    float32_t *dct_inout = mel_logs;
    float32_t *dct_buffer = pDst + n_mels;
    plp_dct2_f32(SDCT, pShift, orthoNorm, dct_inout, dct_buffer, dct_inout);
}

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Updated on 2023-03-01 at 16:16:33 +0000