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transcribe_multichannel.py
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# Copyright 2019 Google LLC
#
# 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.
"""Google Cloud Speech API sample that demonstrates multichannel recognition.
"""
# [START speech_transcribe_multichannel]
from google.cloud import speech
def transcribe_file_with_multichannel(audio_file: str) -> speech.RecognizeResponse:
"""Transcribe the given audio file synchronously with multi channel.
Args:
audio_file (str): Path to the local audio file to be transcribed.
Example: "resources/multi.wav"
Returns:
cloud_speech.RecognizeResponse: The full response object which includes the transcription results.
"""
client = speech.SpeechClient()
with open(audio_file, "rb") as f:
audio_content = f.read()
audio = speech.RecognitionAudio(content=audio_content)
config = speech.RecognitionConfig(
encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
sample_rate_hertz=44100,
language_code="en-US",
audio_channel_count=2,
enable_separate_recognition_per_channel=True,
)
response = client.recognize(config=config, audio=audio)
for i, result in enumerate(response.results):
alternative = result.alternatives[0]
print("-" * 20)
print(f"First alternative of result {i}")
print(f"Transcript: {alternative.transcript}")
print(f"Channel Tag: {result.channel_tag}")
return result
# [END speech_transcribe_multichannel]
def transcribe_gcs_with_multichannel(audio_uri: str) -> speech.RecognizeResponse:
"""Transcribe the given audio file from Google Cloud Storage synchronously with multichannel.
Args:
audio_uri (str): The Cloud Storage URI of the input audio.
E.g., gs://cloud-samples-data/speech/multi.wav
Returns:
speech.RecognizeResponse: The full response object which includes the transcription results.
"""
# [START speech_transcribe_multichannel_gcs]
from google.cloud import speech
client = speech.SpeechClient()
audio = speech.RecognitionAudio(uri=audio_uri)
config = speech.RecognitionConfig(
encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
sample_rate_hertz=44100,
language_code="en-US",
audio_channel_count=2,
enable_separate_recognition_per_channel=True,
)
response = client.recognize(config=config, audio=audio)
for i, result in enumerate(response.results):
alternative = result.alternatives[0]
print("-" * 20)
print(f"First alternative of result {i}")
print(f"Transcript: {alternative.transcript}")
print(f"Channel Tag: {result.channel_tag}")
return result
# [END speech_transcribe_multichannel_gcs]
if __name__ == "__main__":
# It could be a local path like: path_to_file = "resources/multi.wav"
path_to_file = "gs://cloud-samples-data/speech/multi.wav"
if path_to_file.startswith("gs://"):
transcribe_gcs_with_multichannel(path_to_file)
else:
transcribe_file_with_multichannel(path_to_file)