Deepspeech - inferring for more audio files and saving the output


Deepspeech - inferring for more audio files and saving the output



I am done with my training on common voice data for deepspeech from Mozilla and now I am able to get output for a single audio .wav file. Below is the command I am using.


.wav


(deepspeech-venv) megha@megha-medion:~/Alu_Meg/DeepSpeech_Alug_Meg/DeepSpeech$ ./deepspeech my_exportdir/model.pb/output_graph.pb models/alphabet.txt myAudio_for_testing.wav



here, myAudio_for_testing.wav is the audio file I am using to get the below output.


TensorFlow: v1.6.0-9-g236f83e
DeepSpeech: v0.1.1-44-gd68fde8
Warning: reading entire model file into memory. Transform model file into an mmapped graph to reduce heap usage.
2018-06-29 14:51:35.832686: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
heritor teay we decide the lunch ha annral limined eddition of y ye com im standmat



heritor teay we decide the lunch ha annral limined eddition of y ye com im standmat



Here are my few questions,



1) The bolded sentence above is the output for my audio. how can I save this so some file?



2) I have around 2000 audio files like this. how can I read 1 by 1 and get output? I tried to write a script in python to read all the .wav audio files I have, but as my deepspeech is using some sources which are kept in a virtual environment, I am not getting how I can I write my deepspeech command inside the script.
Can you guys give me some hints to proceed with? It will be a great help.



Thank you:)



Megha




1 Answer
1



I found a solution for my first question. we can just redirect the output to some file as below.


(deepspeech-venv) megha@megha-medion:~/Alu_Meg/DeepSpeech_Alug_Meg/DeepSpeech$ ./deepspeech my_exportdir/model.pb/output_graph.pb models/alphabet.txt myAudio_for_testing.wav > output_test.csv
TensorFlow: v1.6.0-9-g236f83e
DeepSpeech: v0.1.1-44-gd68fde8
Warning: reading entire model file into memory. Transform model file into an mmapped graph to reduce heap usage.
2018-06-29 15:22:50.275833: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA



I just added > output_test.csv after my command.



But I still could not figure out with my second question.






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