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1 /* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
2 
3 Licensed under the Apache License, Version 2.0 (the "License");
4 you may not use this file except in compliance with the License.
5 You may obtain a copy of the License at
6 
7     http://www.apache.org/licenses/LICENSE-2.0
8 
9 Unless required by applicable law or agreed to in writing, software
10 distributed under the License is distributed on an "AS IS" BASIS,
11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 See the License for the specific language governing permissions and
13 limitations under the License.
14 ==============================================================================*/
15 
16 // Class for generating spectrogram slices from a waveform.
17 // Initialize() should be called before calls to other functions.  Once
18 // Initialize() has been called and returned true, The Compute*() functions can
19 // be called repeatedly with sequential input data (ie. the first element of the
20 // next input vector directly follows the last element of the previous input
21 // vector). Whenever enough audio samples are buffered to produce a
22 // new frame, it will be placed in output. Output is cleared on each
23 // call to Compute*(). This class is thread-unsafe, and should only be
24 // called from one thread at a time.
25 // With the default parameters, the output of this class should be very
26 // close to the results of the following MATLAB code:
27 // overlap_samples = window_length_samples - step_samples;
28 // window = hann(window_length_samples, 'periodic');
29 // S = abs(spectrogram(audio, window, overlap_samples)).^2;
30 
31 #ifndef TENSORFLOW_CORE_KERNELS_SPECTROGRAM_H_
32 #define TENSORFLOW_CORE_KERNELS_SPECTROGRAM_H_
33 
34 #include <complex>
35 #include <deque>
36 #include <vector>
37 
38 #include "third_party/fft2d/fft.h"
39 #include "tensorflow/core/framework/op_kernel.h"
40 #include "tensorflow/core/framework/tensor.h"
41 
42 namespace tensorflow {
43 
44 class Spectrogram {
45  public:
Spectrogram()46   Spectrogram() : initialized_(false) {}
~Spectrogram()47   ~Spectrogram() {}
48 
49   // Initializes the class with a given window length and step length
50   // (both in samples). Internally a Hann window is used as the window
51   // function. Returns true on success, after which calls to Process()
52   // are possible. window_length must be greater than 1 and step
53   // length must be greater than 0.
54   bool Initialize(int window_length, int step_length);
55 
56   // Initialize with an explicit window instead of a length.
57   bool Initialize(const std::vector<double>& window, int step_length);
58 
59   // Processes an arbitrary amount of audio data (contained in input)
60   // to yield complex spectrogram frames. After a successful call to
61   // Initialize(), Process() may be called repeatedly with new input data
62   // each time.  The audio input is buffered internally, and the output
63   // vector is populated with as many temporally-ordered spectral slices
64   // as it is possible to generate from the input.  The output is cleared
65   // on each call before the new frames (if any) are added.
66   //
67   // The template parameters can be float or double.
68   template <class InputSample, class OutputSample>
69   bool ComputeComplexSpectrogram(
70       const std::vector<InputSample>& input,
71       std::vector<std::vector<std::complex<OutputSample>>>* output);
72 
73   // This function works as the one above, but returns the power
74   // (the L2 norm, or the squared magnitude) of each complex value.
75   template <class InputSample, class OutputSample>
76   bool ComputeSquaredMagnitudeSpectrogram(
77       const std::vector<InputSample>& input,
78       std::vector<std::vector<OutputSample>>* output);
79 
80   // Return reference to the window function used internally.
GetWindow()81   const std::vector<double>& GetWindow() const { return window_; }
82 
83   // Return the number of frequency channels in the spectrogram.
output_frequency_channels()84   int output_frequency_channels() const { return output_frequency_channels_; }
85 
86  private:
87   template <class InputSample>
88   bool GetNextWindowOfSamples(const std::vector<InputSample>& input,
89                               int* input_start);
90   void ProcessCoreFFT();
91 
92   int fft_length_;
93   int output_frequency_channels_;
94   int window_length_;
95   int step_length_;
96   bool initialized_;
97   int samples_to_next_step_;
98 
99   std::vector<double> window_;
100   std::vector<double> fft_input_output_;
101   std::deque<double> input_queue_;
102 
103   // Working data areas for the FFT routines.
104   std::vector<int> fft_integer_working_area_;
105   std::vector<double> fft_double_working_area_;
106 
107   TF_DISALLOW_COPY_AND_ASSIGN(Spectrogram);
108 };
109 
110 }  // namespace tensorflow
111 
112 #endif  // TENSORFLOW_CORE_KERNELS_SPECTROGRAM_H_
113