python-docs-samples/speech/api/speech_streaming.py at numpy · alonsnir/python-docs-samples · GitHub

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#!/usr/bin/python

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

# http://www.apache.org/licenses/LICENSE-2.0

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

"""Sample that streams audio to the Google Cloud Speech API via GRPC."""

from __future__ import division

import contextlib

import re

import threading

from gcloud.credentials import get_credentials

from google.cloud.speech.v1beta1 import cloud_speech_pb2 as cloud_speech

from google.rpc import code_pb2

from grpc.beta import implementations

import pyaudio

# Audio recording parameters

RATE = 16000

CHANNELS = 1

CHUNK = int(RATE / 10) # 100ms

# Keep the request alive for this many seconds

DEADLINE_SECS = 8 * 60 * 60

SPEECH_SCOPE = 'https://www.googleapis.com/auth/cloud-platform'

def make_channel(host, port):

"""Creates an SSL channel with auth credentials from the environment."""

# In order to make an https call, use an ssl channel with defaults

ssl_channel = implementations.ssl_channel_credentials(None, None, None)

# Grab application default credentials from the environment

creds = get_credentials().create_scoped([SPEECH_SCOPE])

# Add a plugin to inject the creds into the header

auth_header = (

'Authorization',

'Bearer ' + creds.get_access_token().access_token)

auth_plugin = implementations.metadata_call_credentials(

lambda _, cb: cb([auth_header], None),

name='google_creds')

# compose the two together for both ssl and google auth

composite_channel = implementations.composite_channel_credentials(

ssl_channel, auth_plugin)

return implementations.secure_channel(host, port, composite_channel)

# [START audio_stream]

@contextlib.contextmanager

def record_audio(channels, rate, chunk):

"""Opens a recording stream in a context manager."""

audio_interface = pyaudio.PyAudio()

audio_stream = audio_interface.open(

format=pyaudio.paInt16, channels=channels, rate=rate,

input=True, frames_per_buffer=chunk,

)

yield audio_stream

audio_stream.stop_stream()

audio_stream.close()

audio_interface.terminate()

# [END audio_stream]

def request_stream(stop_audio, channels=CHANNELS, rate=RATE, chunk=CHUNK):

"""Yields `StreamingRecognizeRequest`s constructed from a recording audio

stream.

Args:

stop_audio: A threading.Event object stops the recording when set.

channels: How many audio channels to record.

rate: The sampling rate in hertz.

chunk: Buffer audio into chunks of this size before sending to the api.

"""

# The initial request must contain metadata about the stream, so the

# server knows how to interpret it.

recognition_config = cloud_speech.RecognitionConfig(

# There are a bunch of config options you can specify. See

# https://goo.gl/A6xv5G for the full list.

encoding='LINEAR16', # raw 16-bit signed LE samples

sample_rate=rate, # the rate in hertz

# See

# https://g.co/cloud/speech/docs/best-practices#language_support

# for a list of supported languages.

language_code='en-US', # a BCP-47 language tag

)

streaming_config = cloud_speech.StreamingRecognitionConfig(

config=recognition_config,

# Note that setting interim_results to True means that you'll likely

# get multiple results for the same bit of audio, as the system

# re-interprets audio in the context of subsequent audio. However, this

# will give us quick results without having to tell the server when to

# finalize a piece of audio.

interim_results=True, single_utterance=True

)

yield cloud_speech.StreamingRecognizeRequest(

streaming_config=streaming_config)

with record_audio(channels, rate, chunk) as audio_stream:

while not stop_audio.is_set():

data = audio_stream.read(chunk)

if not data:

raise StopIteration()

# Subsequent requests can all just have the content

yield cloud_speech.StreamingRecognizeRequest(audio_content=data)

def listen_print_loop(recognize_stream):

for resp in recognize_stream:

if resp.error.code != code_pb2.OK:

raise RuntimeError('Server error: ' + resp.error.message)

# Display the transcriptions & their alternatives

for result in resp.results:

print(result.alternatives)

# Exit recognition if any of the transcribed phrases could be

# one of our keywords.

if any(re.search(r'\b(exit|quit)\b', alt.transcript)

for result in resp.results

for alt in result.alternatives):

print('Exiting..')

return

def main():

stop_audio = threading.Event()

with cloud_speech.beta_create_Speech_stub(

make_channel('speech.googleapis.com', 443)) as service:

try:

listen_print_loop(

service.StreamingRecognize(

request_stream(stop_audio), DEADLINE_SECS))

finally:

# Stop the request stream once we're done with the loop - otherwise

# it'll keep going in the thread that the grpc lib makes for it..

stop_audio.set()

if __name__ == '__main__':

main()

python-docs-samples/speech/api/speech_streaming.py at numpy · alonsnir/python-docs-samples · GitHub

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