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955cf35d5f
The algorithm is based on Hannun's paper: First-Pass Large Vocabulary Continuous Speech Recognition using Bi-Directional Recurrent DNNs
84 lines
2.2 KiB
C++
84 lines
2.2 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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// Code is borrowed from https://github.com/kaldi-asr/kaldi/blob/master/src/base/kaldi-math.h
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// base/kaldi-math.h
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// Copyright 2009-2011 Ondrej Glembek; Microsoft Corporation; Yanmin Qian;
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// Jan Silovsky; Saarland University
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//
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// See ../../COPYING for clarification regarding multiple authors
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
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// WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
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// MERCHANTABLITY OR NON-INFRINGEMENT.
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// See the Apache 2 License for the specific language governing permissions and
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// limitations under the License.
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#ifndef __OPENCV_DNN_MATH_UTILS_HPP__
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#define __OPENCV_DNN_MATH_UTILS_HPP__
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#ifdef OS_QNX
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#include <math.h>
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#else
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#include <cmath>
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#endif
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#include <limits>
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#ifndef FLT_EPSILON
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#define FLT_EPSILON 1.19209290e-7f
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#endif
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namespace cv { namespace dnn {
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const float kNegativeInfinity = -std::numeric_limits<float>::infinity();
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const float kMinLogDiffFloat = std::log(FLT_EPSILON);
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#if !defined(_MSC_VER) || (_MSC_VER >= 1700)
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inline float Log1p(float x) { return log1pf(x); }
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#else
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inline float Log1p(float x) {
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const float cutoff = 1.0e-07;
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if (x < cutoff)
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return x - 2 * x * x;
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else
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return Log(1.0 + x);
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}
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#endif
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inline float Exp(float x) { return expf(x); }
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inline float LogAdd(float x, float y) {
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float diff;
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if (x < y) {
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diff = x - y;
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x = y;
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} else {
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diff = y - x;
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}
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// diff is negative. x is now the larger one.
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if (diff >= kMinLogDiffFloat) {
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float res;
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res = x + Log1p(Exp(diff));
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return res;
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} else {
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return x; // return the larger one.
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}
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}
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}} // namespace
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#endif // __OPENCV_DNN_MATH_UTILS_HPP__
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