Storing output from inference

[JRMeyer]

>>> DJ-Hay
[January 15, 2018, 4:54pm]

Hello,

I am currently running Deepspeech with a virtual environment on Linux
and can get decently accurate transcriptions of my sound files (there
are some technical words that aren't being picked up on). However, my
current analysis is to just look at the command line print statements.
Is there a way to output the results of:

deepspeech models/output_graph.pb my_audio_file.wav models/alphabet.txt
models/lm.binary models/trie

to a text file? I'd ideally like to place multiple outputs from
different chronological short wav files so the transcript would be one
long transcript for the larger wav file the short ones came from.

I figured this would have already been answered, but I can't find an
answer within the Mozilla forums or the feature requests/issues on
github.

Thanks!

[This is an archived TTS discussion thread from discourse.mozilla.org/t/storing-output-from-inference]

[JRMeyer]

>>> reuben
[January 15, 2018, 7:44pm]

Just redirect output to a file:

deepspeech models/output_graph.pb my_audio_file.wav models/alphabet.txt models/lm.binary models/trie >> text_file.txt

This should append the transcriptions to the end of text_file.txt.

[Archived Post]

[JRMeyer]

>>> yv001
[January 15, 2018, 8:15pm]

Although that's possible, having a batch mode allowing to process
several wavs at once rather than initializing the model for each wav
separately would be useful.

Correct me if I am wrong but I suspect that currently the easiest way to
achieve that without recompiling deepseech from source is to fiddle with
installed python script deepspeech/client.py and wrap the inference part
in a loop.

It can be found by running slash
pip install --verbose deepspeech

[Archived Post]

[JRMeyer]

>>> DJ-Hay
[January 15, 2018, 8:36pm]

I don't have my linux on me, but I presume you are speaking of
DeepSpeech/native_client/python/client.py within the github
(https://github.com/mozilla/DeepSpeech/blob/master/native_client/python/client.py).

I'm much better at python than I am at command line commands, so I
believe I can work through that and have python search the appropriate
space for all wav files to make inferences on. One thing I know
offhandedly is that getting python to recognize files in a different
folder is a bit wonky, so can I run a command like:

python path_to_client/modified_client.py path_to_pretrained_model/output_graph.pb path_to_pretrained_model/alphabet.txt path_to_pretrained_model/lm.binary path_to_pretrained_model/trie

while currently in the folder that contains all my wav files, then have
the modified_client.py grab all wav files in the folder and run
inference on them?

[Archived Post]

[JRMeyer]

>>> DJ-Hay
[January 15, 2018, 8:37pm]

Ah, I knew it'd be stupidly simple. Thanks!

[Archived Post]

[JRMeyer]

>>> yv001
[January 15, 2018, 10:50pm]

I think it should work in principle. Getting a list of files in given
directory and passing them to the wav reader + deepspeech (basically
what lines 66-73 in the file you have found do) is not specific to
deepspeech and you should be able to find many examples on python
forums.

[Archived Post]