Speex编码Filter源代码

/* Copyright (C) 2003-2006 Jean-Marc Valin File: mdf.c Echo canceller based on the MDF algorithm (see below) Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. The name of the author may not be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ /* The echo canceller is based on the MDF algorithm described in: J. S. Soo, K. K. Pang Multidelay block frequency adaptive filter, IEEE Trans. Acoust. Speech Signal Process., Vol. ASSP-38, No. 2, February 1990. We use the Alternatively Updated MDF (AUMDF) variant. Robustness to double-talk is achieved using a variable learning rate as described in: Valin, J.-M., On Adjusting the Learning Rate in Frequency Domain Echo Cancellation With Double-Talk. Submitted to IEEE Transactions on Speech and Audio Processing, 2006. There is no explicit double-talk detection, but a continuous variation in the learning rate based on residual echo, double-talk and background noise. About the fixed-point version: All the signals are represented with 16-bit words. The filter weights are represented with 32-bit words, but only the top 16 bits are used in most cases. The lower 16 bits are completely unreliable (due to the fact that the update is done only on the top bits), but help in the adaptation -- probably by removing a "threshold effect" due to quantization (rounding going to zero) when the gradient is small. Another kludge that seems to work good: when performing the weight update, we only move half the way toward the "goal" this seems to reduce the effect of quantization noise in the update phase. This can be seen as applying a gradient descent on a "soft constraint" instead of having a hard constraint. */ #ifdef HAVE_CONFIG_H #include "config.h" #endif #include "misc.h" #include "speex/speex_echo.h" #include "fftwrap.h" #include "pseudofloat.h" #include "math_approx.h" #ifndef M_PI #define M_PI 3.14159265358979323846 #endif #define min(a,b) ((a)<(b) ? (a) : (b)) #define max(a,b) ((a)>(b) ? (a) : (b)) #ifdef FIXED_POINT #define WEIGHT_SHIFT 11 #define NORMALIZE_SCALEDOWN 5 #define NORMALIZE_SCALEUP 3 #else #define WEIGHT_SHIFT 0 #endif #ifdef FIXED_POINT static const spx_float_t MIN_LEAK = ((spx_float_t){16777, -24}); #define TOP16(x) ((x)>>16) #else static const spx_float_t MIN_LEAK = .001f; #define TOP16(x) (x) #endif /** Speex echo cancellation state. */ struct SpeexEchoState_ { int frame_size; /**< Number of samples processed each time */ int window_size; int M; int cancel_count; int adapted; spx_int32_t sampling_rate; spx_word16_t spec_average; spx_word16_t beta0; spx_word16_t beta_max; spx_word32_t sum_adapt; spx_word16_t *e; spx_word16_t *x; spx_word16_t *X; spx_word16_t *d; spx_word16_t *y; spx_word16_t *last_y; spx_word32_t *Yps; spx_word16_t *Y; spx_word16_t *E; spx_word32_t *PHI; spx_word32_t *W; spx_word32_t *power; spx_float_t *power_1; spx_word16_t *wtmp; #ifdef FIXED_POINT spx_word16_t *wtmp2; #endif spx_word32_t *Rf; spx_word32_t *Yf; spx_word32_t *Xf; spx_word32_t *Eh; spx_word32_t *Yh; spx_float_t Pey; spx_float_t Pyy; spx_word16_t *window; void *fft_table; spx_word16_t memX, memD, memE; spx_word16_t preemph; spx_word16_t notch_radius; spx_mem_t notch_mem[2]; }; static inline void filter_dc_notch16(spx_int16_t *in, spx_word16_t radius, spx_word16_t *out, int len, spx_mem_t *mem) { int i; spx_word16_t den2; #ifdef FIXED_POINT den2 = MULT16_16_Q15(radius,radius) + MULT16_16_Q15(QCONST16(.7,15),MULT16_16_Q15(32767-radius,32767-radius)); #else den2 = radius*radius + .7*(1-radius)*(1-radius); #endif /*printf ("%d %d %d %d %d %d\n", num[0], num[1], num[2], den[0], den[1], den[2]);*/ for (i=0;i<len;i++) { spx_word16_t vin = in[i]; spx_word32_t vout = mem[0] + SHL32(EXTEND32(vin),15); #ifdef FIXED_POINT mem[0] = mem[1] + SHL32(SHL32(-EXTEND32(vin),15) + MULT16_32_Q15(radius,vout),1); #else mem[0] = mem[1] + 2*(-vin + radius*vout); #endif mem[1] = SHL32(EXTEND32(vin),15) - MULT16_32_Q15(den2,vout); out[i] = SATURATE32(PSHR32(MULT16_32_Q15(radius,vout),15),32767); } } static inline spx_word32_t inner_prod(const spx_word16_t *x, const spx_word16_t *y, int len) { spx_word32_t sum=0; len >>= 2; while(len--) { spx_word32_t part=0; part = MAC16_16(part,*x++,*y++); part = MAC16_16(part,*x++,*y++); part = MAC16_16(part,*x++,*y++); part = MAC16_16(part,*x++,*y++); /* HINT: If you had a 40-bit accumulator, you could shift only at the end */ sum = ADD32(sum,SHR32(part,6)); } return sum; } /** Compute power spectrum of a half-complex (packed) vector */ static inline void power_spectrum(spx_word16_t *X, spx_word32_t *ps, int N) { int i, j; ps[0]=MULT16_16(X[0],X[0]); for (i=1,j=1;i<N-1;i+=2,j++) { ps[j] = MULT16_16(X[i],X[i]) + MULT16_16(X[i+1],X[i+1]); } ps[j]=MULT16_16(X[i],X[i]); } /** Compute cross-power spectrum of a half-complex (packed) vectors and add to acc */ #ifdef FIXED_POINT static inline void spectral_mul_accum(spx_word16_t *X, spx_word32_t *Y, spx_word16_t *acc, int N, int M) { int i,j; spx_word32_t tmp1=0,tmp2=0; for (j=0;j<M;j++) { tmp1 = MAC16_16(tmp1, X[j*N],TOP16(Y[j*N])); } acc[0] = PSHR32(tmp1,WEIGHT_SHIFT); for (i=1;i<N-1;i+=2) { tmp1 = tmp2 = 0; for (j=0;j<M;j++) { tmp1 = SUB32(MAC16_16(tmp1, X[j*N+i],TOP16(Y[j*N+i])), MULT16_16(X[j*N+i+1],TOP16(Y[j*N+i+1]))); tmp2 = MAC16_16(MAC16_16(tmp2, X[j*N+i+1],TOP16(Y[j*N+i])), X[j*N+i], TOP16(Y[j*N+i+1])); } acc[i] = PSHR32(tmp1,WEIGHT_SHIFT); acc[i+1] = PSHR32(tmp2,WEIGHT_SHIFT); } tmp1 = tmp2 = 0; for (j=0;j<M;j++) { tmp1 = MAC16_16(tmp1, X[(j+1)*N-1],TOP16(Y[(j+1)*N-1])); } acc[N-1] = PSHR32(tmp1,WEIGHT_SHIFT); } #else static inline void spectral_mul_accum(spx_word16_t *X, spx_word32_t *Y, spx_word16_t *acc, int N, int M) { int i,j; for (i=0;i<N;i++) acc[i] = 0; for (j=0;j<M;j++) { acc[0] += X[0]*Y[0]; for (i=1;i<N-1;i+=2) { acc[i] += (X[i]*Y[i] - X[i+1]*Y[i+1]); acc[i+1] += (X[i+1]*Y[i] + X[i]*Y[i+1]); } acc[i] += X[i]*Y[i]; X += N; Y += N; } } #endif /** Compute weighted cross-power spectrum of a half-complex (packed) vector with conjugate */ static inline void weighted_spectral_mul_conj(spx_float_t *w, spx_word16_t *X, spx_word16_t *Y, spx_word32_t *prod, int N) { int i, j; prod[0] = FLOAT_MUL32(w[0],MULT16_16(X[0],Y[0])); for (i=1,j=1;i<N