Transcribe a local file with recognition metadata (beta)

/**
 * Transcribe the given audio file and include recognition metadata in the request.
 *
 * @param fileName the path to an audio file.
 */
publicstaticvoidtranscribeFileWithMetadata(StringfileName)throwsException{
Pathpath=Paths.get(fileName);
byte[]content=Files.readAllBytes(path);
try(SpeechClientspeechClient=SpeechClient.create()){
// Get the contents of the local audio file
RecognitionAudiorecognitionAudio=
RecognitionAudio.newBuilder().setContent(ByteString.copyFrom(content)).build();
// Construct a recognition metadata object.
// Most metadata fields are specified as enums that can be found
// in speech.enums.RecognitionMetadata
RecognitionMetadatametadata=
RecognitionMetadata.newBuilder()
.setInteractionType(InteractionType.DISCUSSION)
.setMicrophoneDistance(MicrophoneDistance.NEARFIELD)
.setRecordingDeviceType(RecordingDeviceType.SMARTPHONE)
.setRecordingDeviceName("Pixel 2 XL")// Some metadata fields are free form strings
// And some are integers, for instance the 6 digit NAICS code
// https://www.naics.com/search/
.setIndustryNaicsCodeOfAudio(519190)
.build();
// Configure request to enable enhanced models
RecognitionConfigconfig=
RecognitionConfig.newBuilder()
.setEncoding(AudioEncoding.LINEAR16)
.setLanguageCode("en-US")
.setSampleRateHertz(8000)
.setMetadata(metadata)// Add the metadata to the config
.build();
// Perform the transcription request
RecognizeResponserecognizeResponse=speechClient.recognize(config,recognitionAudio);
// Print out the results
for(SpeechRecognitionResultresult:recognizeResponse.getResultsList()){
// There can be several alternative transcripts for a given chunk of speech. Just use the
// first (most likely) one here.
SpeechRecognitionAlternativealternative=result.getAlternatives(0);
System.out.format("Transcript: %s\n\n",alternative.getTranscript());
}
}
}

// Imports the Google Cloud client library for Beta API
/**
 * TODO(developer): Update client library import to use new
 * version of API when desired features become available
 */
constspeech=require('@google-cloud/speech').v1p1beta1;
constfs=require('fs');
// Creates a client
constclient=newspeech.SpeechClient ();
asyncfunctionsyncRecognizeWithMetaData(){
/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const filename = 'Local path to audio file, e.g. /path/to/audio.raw';
// const encoding = 'Encoding of the audio file, e.g. LINEAR16';
// const sampleRateHertz = 16000;
// const languageCode = 'BCP-47 language code, e.g. en-US';
constrecognitionMetadata={
interactionType:'DISCUSSION',
microphoneDistance:'NEARFIELD',
recordingDeviceType:'SMARTPHONE',
recordingDeviceName:'Pixel 2 XL',
industryNaicsCodeOfAudio:519190,
};
constconfig={
encoding:encoding,
sampleRateHertz:sampleRateHertz,
languageCode:languageCode,
metadata:recognitionMetadata,
};
constaudio={
content:fs.readFileSync(filename).toString('base64'),
};
constrequest={
config:config,
audio:audio,
};
// Detects speech in the audio file
const[response]=awaitclient.recognize(request);
response.results.forEach(result=>{
constalternative=result.alternatives[0];
console.log(alternative.transcript);
});

fromgoogle.cloudimport speech_v1p1beta1 as speech
client = speech.SpeechClient()
speech_file = "resources/commercial_mono.wav"
with open(speech_file, "rb") as audio_file:
 content = audio_file.read()
# Here we construct a recognition metadata object.
# Most metadata fields are specified as enums that can be found
# in speech.enums.RecognitionMetadata
metadata = speech.RecognitionMetadata()
metadata.interaction_type = speech.RecognitionMetadata.InteractionType.DISCUSSION
metadata.microphone_distance = (
 speech.RecognitionMetadata.MicrophoneDistance.NEARFIELD
)
metadata.recording_device_type = (
 speech.RecognitionMetadata.RecordingDeviceType.SMARTPHONE
)
# Some metadata fields are free form strings
metadata.recording_device_name = "Pixel 2 XL"
# And some are integers, for instance the 6 digit NAICS code
# https://www.naics.com/search/
metadata.industry_naics_code_of_audio = 519190
audio = speech.RecognitionAudio(content=content)
config = speech.RecognitionConfig(
 encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
 sample_rate_hertz=8000,
 language_code="en-US",
 # Add this in the request to send metadata.
 metadata=metadata,
)
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}")
return response.results