Chirp 3 Transcription: Enhanced multilingual accuracy

  import 
  
 os 
 from 
  
 google.cloud.speech_v2 
  
 import 
 SpeechClient 
 from 
  
 google.cloud.speech_v2.types 
  
 import 
 cloud_speech 
 from 
  
 google.api_core.client_options 
  
 import 
 ClientOptions 
 PROJECT_ID 
 = 
 os 
 . 
 getenv 
 ( 
 "GOOGLE_CLOUD_PROJECT" 
 ) 
 def 
  
 transcribe_batch_chirp3 
 ( 
 audio_uri 
 : 
 str 
 , 
 ) 
 - 
> cloud_speech 
 . 
 BatchRecognizeResults 
 : 
  
 """Transcribes an audio file from a Google Cloud Storage URI using the Chirp 3 model of Google Cloud Speech-to-Text V2 API. 
 Args: 
 audio_uri (str): The Google Cloud Storage URI of the input 
 audio file. E.g., gs://[BUCKET]/[FILE] 
 Returns: 
 cloud_speech.RecognizeResponse: The response from the 
 Speech-to-Text API containing the transcription results. 
 """ 
 # Instantiates a client 
 client 
 = 
 SpeechClient 
 ( 
 client_options 
 = 
 ClientOptions 
 ( 
 api_endpoint 
 = 
 "us-west1-speech.googleapis.com" 
 , 
 ) 
 ) 
 speaker_diarization_config 
 = 
 cloud_speech 
 . 
 SpeakerDiarizationConfig 
 ( 
 min_speaker_count 
 = 
 1 
 , 
 # minimum number of speakers 
 max_speaker_count 
 = 
 6 
 , 
 # maximum expected number of speakers 
 ) 
 config 
 = 
 cloud_speech 
 . 
 RecognitionConfig 
 ( 
 auto_decoding_config 
 = 
 cloud_speech 
 . 
 AutoDetectDecodingConfig 
 (), 
 language_codes 
 = 
 [ 
 "en-US" 
 ], 
 # Use "auto" to detect language 
 model 
 = 
 "chirp_3" 
 , 
 features 
 = 
 cloud_speech 
 . 
 RecognitionFeatures 
 ( 
 diarization_config 
 = 
 speaker_diarization_config 
 , 
 ), 
 ) 
 file_metadata 
 = 
 cloud_speech 
 . 
 BatchRecognizeFileMetadata 
 ( 
 uri 
 = 
 audio_uri 
 ) 
 request 
 = 
 cloud_speech 
 . 
 BatchRecognizeRequest 
 ( 
 recognizer 
 = 
 f 
 "projects/ 
 { 
 PROJECT_ID 
 } 
 /locations/us-west1/recognizers/_" 
 , 
 config 
 = 
 config 
 , 
 files 
 = 
 [ 
 file_metadata 
 ], 
 recognition_output_config 
 = 
 cloud_speech 
 . 
 RecognitionOutputConfig 
 ( 
 inline_response_config 
 = 
 cloud_speech 
 . 
 InlineOutputConfig 
 (), 
 ), 
 ) 
 # Transcribes the audio into text 
 operation 
 = 
 client 
 . 
 batch_recognize 
 ( 
 request 
 = 
 request 
 ) 
 print 
 ( 
 "Waiting for operation to complete..." 
 ) 
 response 
 = 
 operation 
 . 
 result 
 ( 
 timeout 
 = 
 120 
 ) 
 for 
 result 
 in 
 response 
 . 
 results 
 [ 
 audio_uri 
 ] 
 . 
 transcript 
 . 
 results 
 : 
 print 
 ( 
 f 
 "Transcript: 
 { 
 result 
 . 
 alternatives 
 [ 
 0 
 ] 
 . 
 transcript 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Detected Language: 
 { 
 result 
 . 
 language_code 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Speakers per word: 
 { 
 result 
 . 
 alternatives 
 [ 
 0 
 ] 
 . 
 words 
 } 
 " 
 ) 
 return 
 response 
 . 
 results 
 [ 
 audio_uri 
 ] 
 . 
 transcript