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Diarization Output Modified #1586

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merged 13 commits into from
Jul 20, 2018
Merged

Diarization Output Modified #1586

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b5d4ceb
Printing the last paragraph only.
happyhuman Jul 19, 2018
a4c2ca4
Python3 print
happyhuman Jul 19, 2018
f7e4131
Removing sample rate setting
happyhuman Jul 20, 2018
5949a81
Merge branch 'master' into diarization-fix
happyhuman Jul 20, 2018
f1662fe
Adding the missing output parameter in the example
happyhuman Jul 20, 2018
4fbefa3
Changes based on the comments
happyhuman Jul 20, 2018
b105e2a
Removed filenames as input parameters
happyhuman Jul 20, 2018
b53296a
Removed unused args
happyhuman Jul 20, 2018
46c1f43
Updated README file
happyhuman Jul 20, 2018
99ed289
Updated the inline comment
happyhuman Jul 20, 2018
3ef4a0d
Modified code to make it more readable
happyhuman Jul 20, 2018
146a180
Simplified the response object processing.
happyhuman Jul 20, 2018
597dc0a
Fixing the long line issue.
happyhuman Jul 20, 2018
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2 changes: 1 addition & 1 deletion speech/cloud-client/README.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -221,7 +221,7 @@ To run this sample:

$ python beta_snippets.py

usage: beta_snippets.py [-h] command path first second
usage: beta_snippets.py [-h] command path [first] [second]

Google Cloud Speech API sample that demonstrates enhanced models
and recognition metadata.
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16 changes: 5 additions & 11 deletions speech/cloud-client/beta_snippets.py
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Expand Up @@ -46,7 +46,6 @@ def transcribe_file_with_enhanced_model(speech_file):
audio = speech.types.RecognitionAudio(content=content)
config = speech.types.RecognitionConfig(
encoding=speech.enums.RecognitionConfig.AudioEncoding.LINEAR16,
sample_rate_hertz=8000,
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Any particular reason for omitting this? For WAV files, the API can infer this, but in the general case it's probably a good idea to include the sample rate

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I keep going back and forth about it. Sometimes it is useful, and other times it is causing an error when the input file has a different sample rate.

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Why is sample_rate removed? I am sure there is good reason.

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We just had a discussion about it with Roy and Jerjou. If the input file has a different sample rate, it will cause an error. It is simpler just to omit it and the API figures it out on its own.

language_code='en-US',
# Enhanced models are only available to projects that
# opt in for audio data collection.
Expand Down Expand Up @@ -95,7 +94,6 @@ def transcribe_file_with_metadata(speech_file):
audio = speech.types.RecognitionAudio(content=content)
config = speech.types.RecognitionConfig(
encoding=speech.enums.RecognitionConfig.AudioEncoding.LINEAR16,
sample_rate_hertz=8000,
language_code='en-US',
# Add this in the request to send metadata.
metadata=metadata)
Expand Down Expand Up @@ -125,7 +123,6 @@ def transcribe_file_with_auto_punctuation(speech_file):
audio = speech.types.RecognitionAudio(content=content)
config = speech.types.RecognitionConfig(
encoding=speech.enums.RecognitionConfig.AudioEncoding.LINEAR16,
sample_rate_hertz=8000,
language_code='en-US',
# Enable automatic punctuation
enable_automatic_punctuation=True)
Expand Down Expand Up @@ -156,21 +153,18 @@ def transcribe_file_with_diarization(speech_file):

config = speech.types.RecognitionConfig(
encoding=speech.enums.RecognitionConfig.AudioEncoding.LINEAR16,
sample_rate_hertz=16000,
language_code='en-US',
enable_speaker_diarization=True,
diarization_speaker_count=2)

print('Waiting for operation to complete...')
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Consider using python logging facility. Understandably, for this sample it might be overkill so take it or leave it.

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FWIW nearly all our other Python samples do print(). It's true that it's not always the recommended practice in production, but it's easy to understand. With logging there's always the risk that the developer has some weird config where the logs end up where maybe they don't expect.

response = client.recognize(config, audio)

for i, result in enumerate(response.results):
alternative = result.alternatives[0]
print('-' * 20)
print('First alternative of result {}: {}'
.format(i, alternative.transcript))
print('Speaker Tag for the first word: {}'
.format(alternative.words[0].speaker_tag))
result = response.results[-1]
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A comment here explaining why you're only taking the last result (instead of all of them) would probably be helpful.

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Good idea. Adding it.

words_info = result.alternatives[0].words
pieces = ['%s (%s)' % (word_info.word, word_info.speaker_tag)
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Isn't '{} ({})'.format(word_info.word, word_info.speaker_tag) the preferred way to do this these days? Or is Thea no longer benevolent overlord?

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Good point. I will modify it.

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pieces is an odd variable name.

for word_info in words_info]
print(' '.join(pieces))
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I feel this might not illustrate the "typical" use case, where the developer might more likely want to group and join the words according to their speaker_tag.

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Interesting point. Tough to say what the right use case is. But I see it just as a sample. to show them the API, and not the use case. Do you think we can keep it as is, or should we change it?

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I agree - in that sense perhaps let's just iterate through words_info and print everything without the nice formatting of '%s (%s)'. the expected output of the test really confused me.

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I think I agree with the way it's formatted but whatever you decide consider this syntax

pieces = ['{} ({})'.format(word_info.word, word_info.speaker_tag) for word_info in words_info]

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I made some changes to make the output to look like this:

Speaker #1: I'm here
Speaker #2: hi I'd like to buy a Chrome Cast and I was wondering whether you could help me

# [END speech_transcribe_diarization]


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4 changes: 2 additions & 2 deletions speech/cloud-client/beta_snippets_test.py
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Expand Up @@ -51,10 +51,10 @@ def test_transcribe_file_with_auto_punctuation(capsys):

def test_transcribe_diarization(capsys):
transcribe_file_with_diarization(
os.path.join(RESOURCES, 'Google_Gnome.wav'))
os.path.join(RESOURCES, 'commercial_mono.wav'))
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Consider adding file name as an argument and not hardcode.

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Even for the unit tests?

out, err = capsys.readouterr()

assert 'OK Google stream stranger things from Netflix to my TV' in out
assert "I'm (1) here (1) hi (2)" in out


def test_transcribe_multichannel_file(capsys):
Expand Down