1 # TensorFlow Spectrogram Example 2 3 This example shows how you can load audio from a .wav file, convert it to a 4 spectrogram, and then save it out as a PNG image. A spectrogram is a 5 visualization of the frequencies in sound over time, and can be useful as a 6 feature for neural network recognition on noise or speech. 7 8 ## Building 9 10 To build it, run this command: 11 12 ```bash 13 bazel build tensorflow/examples/wav_to_spectrogram/... 14 ``` 15 16 That should build a binary executable that you can then run like this: 17 18 ```bash 19 bazel-bin/tensorflow/examples/wav_to_spectrogram/wav_to_spectrogram 20 ``` 21 22 This uses a default test audio file that's part of the TensorFlow source code, 23 and writes out the image to the current directory as spectrogram.png. 24 25 ## Options 26 27 To load your own audio, you need to supply a .wav file in LIN16 format, and use 28 the `--input_audio` flag to pass in the path. 29 30 To control how the spectrogram is created, you can specify the `--window_size` 31 and `--stride` arguments, which control how wide the window used to estimate 32 frequencies is, and how widely adjacent windows are spaced. 33 34 The `--output_image` flag sets the path to save the image file to. This is 35 always written out in PNG format, even if you specify a different file 36 extension. 37 38 If your result seems too dark, try using the `--brightness` flag to make the 39 output image easier to see. 40 41 Here's an example of how to use all of them together: 42 43 ```bash 44 bazel-bin/tensorflow/examples/wav_to_spectrogram/wav_to_spectrogram \ 45 --input_wav=/tmp/my_audio.wav \ 46 --window=1024 \ 47 --stride=512 \ 48 --output_image=/tmp/my_spectrogram.png 49 ``` 50
