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.
(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
For my 2nd question, I added an extra section in client.py file of Deepspeech to encounter a number of files and save each transcripts in an excel file with the corresponding file name as an index value.
> r =csv.reader(open('my_CSV_file.csv')) lines = list(r) pathToAudio =
> args.audio#sys.argv[3] audio_files = os.listdir(pathToAudio) for i in
> range(1,len(lines)):
> for eachfile in audio_files :
> if eachfile.endswith(".wav"):
> if(eachfile == lines[i][1]):
> file_Path = pathToAudio + "/" + eachfile
> print("File to be read is ", file_Path)
> fs, audio = wav.read(file_Path)
> audio_length = len(audio) * ( 1 / 16000)
> assert fs == 16000, "Only 16000Hz input WAV files are supported for now!"
> print('Running inference.', file=sys.stderr)
> inference_start = timer()
> output = ds.stt(audio, fs)
> lines[i][2] = output
> writer = csv.writer(open('my_CSV_file', 'w'))
> writer.writerows(lines)
> print(output)
> inference_end = timer() - inference_start
> print('Inference took %0.3fs for %0.3fs audio file.' % (inference_end, audio_length), file=sys.stderr)