Add RNN for VAD and speech/music classification

Based on two dense layers with a GRU layer in the middle

1 files changed, 0 insertions, 86 deletions

diff --git a/src/mlp_train.h b/src/mlp_train.h
deleted file mode 100644
index 49404158..00000000
--- a/src/mlp_train.h
+++ /dev/null
@@ -1,86 +0,0 @@
-/* Copyright (c) 2008-2011 Octasic Inc.
-   Written by Jean-Marc Valin */
-/*
-   Redistribution and use in source and binary forms, with or without
-   modification, are permitted provided that the following conditions
-   are met:
-
-   - Redistributions of source code must retain the above copyright
-   notice, this list of conditions and the following disclaimer.
-
-   - 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.
-
-   THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-   ``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 FOUNDATION OR
-   CONTRIBUTORS 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.
-*/
-
-#ifndef _MLP_TRAIN_H_
-#define _MLP_TRAIN_H_
-
-#include <math.h>
-#include <stdlib.h>
-
-double tansig_table[501];
-static inline double tansig_double(double x)
-{
-    return 2./(1.+exp(-2.*x)) - 1.;
-}
-static inline void build_tansig_table(void)
-{
-    int i;
-    for (i=0;i<501;i++)
-        tansig_table[i] = tansig_double(.04*(i-250));
-}
-
-static inline double tansig_approx(double x)
-{
-    int i;
-    double y, dy;
-    if (x>=10)
-        return 1;
-    if (x<=-10)
-        return -1;
-    i = lrint(25*x);
-    x -= .04*i;
-    y = tansig_table[250+i];
-    dy = 1-y*y;
-    y = y + x*dy*(1 - y*x);
-    return y;
-}
-
-static inline float randn(float sd)
-{
-   float U1, U2, S, x;
-   do {
-      U1 = ((float)rand())/RAND_MAX;
-      U2 = ((float)rand())/RAND_MAX;
-      U1 = 2*U1-1;
-      U2 = 2*U2-1;
-      S = U1*U1 + U2*U2;
-   } while (S >= 1 || S == 0.0f);
-   x = sd*sqrt(-2 * log(S) / S) * U1;
-   return x;
-}
-
-
-typedef struct {
-    int layers;
-    int *topo;
-    double **weights;
-    double **best_weights;
-    double *in_rate;
-} MLPTrain;
-
-
-#endif /* _MLP_TRAIN_H_ */