Chirp 2: 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_streaming_chirp2 
 ( 
 audio_file 
 : 
 str 
 ) 
 - 
> cloud_speech 
 . 
 StreamingRecognizeResponse 
 : 
  
 """Transcribes audio from audio file stream using the Chirp 2 model of Google Cloud Speech-to-Text V2 API. 
 Args: 
 audio_file (str): Path to the local audio file to be transcribed. 
 Example: "resources/audio.wav" 
 Returns: 
 cloud_speech.RecognizeResponse: The response from the Speech-to-Text API V2 containing 
 the transcription results. 
 """ 
 # Instantiates a client 
 client 
 = 
 SpeechClient 
 ( 
 client_options 
 = 
 ClientOptions 
 ( 
 api_endpoint 
 = 
 "us-central1-speech.googleapis.com" 
 , 
 ) 
 ) 
 # Reads a file as bytes 
 with 
 open 
 ( 
 audio_file 
 , 
 "rb" 
 ) 
 as 
 f 
 : 
 content 
 = 
 f 
 . 
 read 
 () 
 # In practice, stream should be a generator yielding chunks of audio data 
 chunk_length 
 = 
 len 
 ( 
 content 
 ) 
 // 
 5 
 stream 
 = 
 [ 
 content 
 [ 
 start 
 : 
 start 
 + 
 chunk_length 
 ] 
 for 
 start 
 in 
 range 
 ( 
 0 
 , 
 len 
 ( 
 content 
 ), 
 chunk_length 
 ) 
 ] 
 audio_requests 
 = 
 ( 
 cloud_speech 
 . 
 StreamingRecognizeRequest 
 ( 
 audio 
 = 
 audio 
 ) 
 for 
 audio 
 in 
 stream 
 ) 
 recognition_config 
 = 
 cloud_speech 
 . 
 RecognitionConfig 
 ( 
 auto_decoding_config 
 = 
 cloud_speech 
 . 
 AutoDetectDecodingConfig 
 (), 
 language_codes 
 = 
 [ 
 "en-US" 
 ], 
 model 
 = 
 "chirp_2" 
 , 
 ) 
 streaming_config 
 = 
 cloud_speech 
 . 
 StreamingRecognitionConfig 
 ( 
 config 
 = 
 recognition_config 
 ) 
 config_request 
 = 
 cloud_speech 
 . 
 StreamingRecognizeRequest 
 ( 
 recognizer 
 = 
 f 
 "projects/ 
 { 
 PROJECT_ID 
 } 
 /locations/us-central1/recognizers/_" 
 , 
 streaming_config 
 = 
 streaming_config 
 , 
 ) 
 def 
  
 requests 
 ( 
 config 
 : 
 cloud_speech 
 . 
 RecognitionConfig 
 , 
 audio 
 : 
 list 
 ) 
 - 
> list 
 : 
 yield 
 config 
 yield from 
 audio 
 # Transcribes the audio into text 
 responses_iterator 
 = 
 client 
 . 
 streaming_recognize 
 ( 
 requests 
 = 
 requests 
 ( 
 config_request 
 , 
 audio_requests 
 ) 
 ) 
 responses 
 = 
 [] 
 for 
 response 
 in 
 responses_iterator 
 : 
 responses 
 . 
 append 
 ( 
 response 
 ) 
 for 
 result 
 in 
 response 
 . 
 results 
 : 
 print 
 ( 
 f 
 "Transcript: 
 { 
 result 
 . 
 alternatives 
 [ 
 0 
 ] 
 . 
 transcript 
 } 
 " 
 ) 
 return 
 responses 
 

  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_sync_chirp2 
 ( 
 audio_file 
 : 
 str 
 ) 
 - 
> cloud_speech 
 . 
 RecognizeResponse 
 : 
  
 """Transcribes an audio file using the Chirp 2 model of Google Cloud Speech-to-Text V2 API. 
 Args: 
 audio_file (str): Path to the local audio file to be transcribed. 
 Example: "resources/audio.wav" 
 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-central1-speech.googleapis.com" 
 , 
 ) 
 ) 
 # Reads a file as bytes 
 with 
 open 
 ( 
 audio_file 
 , 
 "rb" 
 ) 
 as 
 f 
 : 
 audio_content 
 = 
 f 
 . 
 read 
 () 
 config 
 = 
 cloud_speech 
 . 
 RecognitionConfig 
 ( 
 auto_decoding_config 
 = 
 cloud_speech 
 . 
 AutoDetectDecodingConfig 
 (), 
 language_codes 
 = 
 [ 
 "en-US" 
 ], 
 model 
 = 
 "chirp_2" 
 , 
 ) 
 request 
 = 
 cloud_speech 
 . 
 RecognizeRequest 
 ( 
 recognizer 
 = 
 f 
 "projects/ 
 { 
 PROJECT_ID 
 } 
 /locations/us-central1/recognizers/_" 
 , 
 config 
 = 
 config 
 , 
 content 
 = 
 audio_content 
 , 
 ) 
 # Transcribes the audio into text 
 response 
 = 
 client 
 . 
 recognize 
 ( 
 request 
 = 
 request 
 ) 
 for 
 result 
 in 
 response 
 . 
 results 
 : 
 print 
 ( 
 f 
 "Transcript: 
 { 
 result 
 . 
 alternatives 
 [ 
 0 
 ] 
 . 
 transcript 
 } 
 " 
 ) 
 return 
 response 
 

  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_chirp2 
 ( 
 audio_uri 
 : 
 str 
 , 
 ) 
 - 
> cloud_speech 
 . 
 BatchRecognizeResults 
 : 
  
 """Transcribes an audio file from a Google Cloud Storage URI using the Chirp 2 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-central1-speech.googleapis.com" 
 , 
 ) 
 ) 
 config 
 = 
 cloud_speech 
 . 
 RecognitionConfig 
 ( 
 auto_decoding_config 
 = 
 cloud_speech 
 . 
 AutoDetectDecodingConfig 
 (), 
 language_codes 
 = 
 [ 
 "en-US" 
 ], 
 model 
 = 
 "chirp_2" 
 , 
 ) 
 file_metadata 
 = 
 cloud_speech 
 . 
 BatchRecognizeFileMetadata 
 ( 
 uri 
 = 
 audio_uri 
 ) 
 request 
 = 
 cloud_speech 
 . 
 BatchRecognizeRequest 
 ( 
 recognizer 
 = 
 f 
 "projects/ 
 { 
 PROJECT_ID 
 } 
 /locations/us-central1/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 
 } 
 " 
 ) 
 return 
 response 
 . 
 results 
 [ 
 audio_uri 
 ] 
 . 
 transcript 
 

  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_sync_chirp2_auto_detect_language 
 ( 
 audio_file 
 : 
 str 
 ) 
 - 
> cloud_speech 
 . 
 RecognizeResponse 
 : 
  
 """Transcribes an audio file and auto-detect spoken language using Chirp 2. 
 Please see https://cloud.google.com/speech-to-text/v2/docs/encoding for more 
 information on which audio encodings are supported. 
 Args: 
 audio_file (str): Path to the local audio file to be transcribed. 
 Example: "resources/audio.wav" 
 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-central1-speech.googleapis.com" 
 , 
 ) 
 ) 
 # Reads a file as bytes 
 with 
 open 
 ( 
 audio_file 
 , 
 "rb" 
 ) 
 as 
 f 
 : 
 audio_content 
 = 
 f 
 . 
 read 
 () 
 config 
 = 
 cloud_speech 
 . 
 RecognitionConfig 
 ( 
 auto_decoding_config 
 = 
 cloud_speech 
 . 
 AutoDetectDecodingConfig 
 (), 
 language_codes 
 = 
 [ 
 "auto" 
 ], 
 # Set language code to auto to detect language. 
 model 
 = 
 "chirp_2" 
 , 
 ) 
 request 
 = 
 cloud_speech 
 . 
 RecognizeRequest 
 ( 
 recognizer 
 = 
 f 
 "projects/ 
 { 
 PROJECT_ID 
 } 
 /locations/us-central1/recognizers/_" 
 , 
 config 
 = 
 config 
 , 
 content 
 = 
 audio_content 
 , 
 ) 
 # Transcribes the audio into text 
 response 
 = 
 client 
 . 
 recognize 
 ( 
 request 
 = 
 request 
 ) 
 for 
 result 
 in 
 response 
 . 
 results 
 : 
 print 
 ( 
 f 
 "Transcript: 
 { 
 result 
 . 
 alternatives 
 [ 
 0 
 ] 
 . 
 transcript 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Detected Language: 
 { 
 result 
 . 
 language_code 
 } 
 " 
 ) 
 return 
 response 
 

  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 
  
 translate_sync_chirp2 
 ( 
 audio_file 
 : 
 str 
 ) 
 - 
> cloud_speech 
 . 
 RecognizeResponse 
 : 
  
 """Translates an audio file using Chirp 2. 
 Args: 
 audio_file (str): Path to the local audio file to be translated. 
 Example: "resources/audio.wav" 
 Returns: 
 cloud_speech.RecognizeResponse: The response from the Speech-to-Text API containing 
 the translated results. 
 """ 
 # Instantiates a client 
 client 
 = 
 SpeechClient 
 ( 
 client_options 
 = 
 ClientOptions 
 ( 
 api_endpoint 
 = 
 "us-central1-speech.googleapis.com" 
 , 
 ) 
 ) 
 # Reads a file as bytes 
 with 
 open 
 ( 
 audio_file 
 , 
 "rb" 
 ) 
 as 
 f 
 : 
 audio_content 
 = 
 f 
 . 
 read 
 () 
 config 
 = 
 cloud_speech 
 . 
 RecognitionConfig 
 ( 
 auto_decoding_config 
 = 
 cloud_speech 
 . 
 AutoDetectDecodingConfig 
 (), 
 language_codes 
 = 
 [ 
 "fr-FR" 
 ], 
 # Set language code to targeted to detect language. 
 translation_config 
 = 
 cloud_speech 
 . 
 TranslationConfig 
 ( 
 target_language 
 = 
 "fr-FR" 
 ), 
 # Set target language code. 
 model 
 = 
 "chirp_2" 
 , 
 ) 
 request 
 = 
 cloud_speech 
 . 
 RecognizeRequest 
 ( 
 recognizer 
 = 
 f 
 "projects/ 
 { 
 PROJECT_ID 
 } 
 /locations/us-central1/recognizers/_" 
 , 
 config 
 = 
 config 
 , 
 content 
 = 
 audio_content 
 , 
 ) 
 # Transcribes the audio into text 
 response 
 = 
 client 
 . 
 recognize 
 ( 
 request 
 = 
 request 
 ) 
 for 
 result 
 in 
 response 
 . 
 results 
 : 
 print 
 ( 
 f 
 "Translated transcript: 
 { 
 result 
 . 
 alternatives 
 [ 
 0 
 ] 
 . 
 transcript 
 } 
 " 
 ) 
 return 
 response 
 

  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_sync_chirp2_with_timestamps 
 ( 
 audio_file 
 : 
 str 
 ) 
 - 
> cloud_speech 
 . 
 RecognizeResponse 
 : 
  
 """Transcribes an audio file using the Chirp 2 model of Google Cloud Speech-to-Text V2 API, providing word-level timestamps for each transcribed word. 
 Args: 
 audio_file (str): Path to the local audio file to be transcribed. 
 Example: "resources/audio.wav" 
 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-central1-speech.googleapis.com" 
 , 
 ) 
 ) 
 # Reads a file as bytes 
 with 
 open 
 ( 
 audio_file 
 , 
 "rb" 
 ) 
 as 
 f 
 : 
 audio_content 
 = 
 f 
 . 
 read 
 () 
 config 
 = 
 cloud_speech 
 . 
 RecognitionConfig 
 ( 
 auto_decoding_config 
 = 
 cloud_speech 
 . 
 AutoDetectDecodingConfig 
 (), 
 language_codes 
 = 
 [ 
 "en-US" 
 ], 
 model 
 = 
 "chirp_2" 
 , 
 features 
 = 
 cloud_speech 
 . 
 RecognitionFeatures 
 ( 
 enable_word_time_offsets 
 = 
 True 
 , 
 # Enabling word-level timestamps 
 ) 
 ) 
 request 
 = 
 cloud_speech 
 . 
 RecognizeRequest 
 ( 
 recognizer 
 = 
 f 
 "projects/ 
 { 
 PROJECT_ID 
 } 
 /locations/us-central1/recognizers/_" 
 , 
 config 
 = 
 config 
 , 
 content 
 = 
 audio_content 
 , 
 ) 
 # Transcribes the audio into text 
 response 
 = 
 client 
 . 
 recognize 
 ( 
 request 
 = 
 request 
 ) 
 for 
 result 
 in 
 response 
 . 
 results 
 : 
 print 
 ( 
 f 
 "Transcript: 
 { 
 result 
 . 
 alternatives 
 [ 
 0 
 ] 
 . 
 transcript 
 } 
 " 
 ) 
 return 
 response 
 

  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_sync_chirp2_model_adaptation 
 ( 
 audio_file 
 : 
 str 
 ) 
 - 
> cloud_speech 
 . 
 RecognizeResponse 
 : 
  
 """Transcribes an audio file using the Chirp 2 model with adaptation, improving accuracy for specific audio characteristics or vocabulary. 
 Args: 
 audio_file (str): Path to the local audio file to be transcribed. 
 Example: "resources/audio.wav" 
 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-central1-speech.googleapis.com" 
 , 
 ) 
 ) 
 # Reads a file as bytes 
 with 
 open 
 ( 
 audio_file 
 , 
 "rb" 
 ) 
 as 
 f 
 : 
 audio_content 
 = 
 f 
 . 
 read 
 () 
 config 
 = 
 cloud_speech 
 . 
 RecognitionConfig 
 ( 
 auto_decoding_config 
 = 
 cloud_speech 
 . 
 AutoDetectDecodingConfig 
 (), 
 language_codes 
 = 
 [ 
 "en-US" 
 ], 
 model 
 = 
 "chirp_2" 
 , 
 # Use model adaptation 
 adaptation 
 = 
 cloud_speech 
 . 
 SpeechAdaptation 
 ( 
 phrase_sets 
 = 
 [ 
 cloud_speech 
 . 
 SpeechAdaptation 
 . 
 AdaptationPhraseSet 
 ( 
 inline_phrase_set 
 = 
 cloud_speech 
 . 
 PhraseSet 
 ( 
 phrases 
 = 
 [ 
 { 
 "value" 
 : 
 "alphabet" 
 , 
 }, 
 { 
 "value" 
 : 
 "cell phone service" 
 , 
 } 
 ]) 
 ) 
 ] 
 ) 
 ) 
 request 
 = 
 cloud_speech 
 . 
 RecognizeRequest 
 ( 
 recognizer 
 = 
 f 
 "projects/ 
 { 
 PROJECT_ID 
 } 
 /locations/us-central1/recognizers/_" 
 , 
 config 
 = 
 config 
 , 
 content 
 = 
 audio_content 
 , 
 ) 
 # Transcribes the audio into text 
 response 
 = 
 client 
 . 
 recognize 
 ( 
 request 
 = 
 request 
 ) 
 for 
 result 
 in 
 response 
 . 
 results 
 : 
 print 
 ( 
 f 
 "Transcript: 
 { 
 result 
 . 
 alternatives 
 [ 
 0 
 ] 
 . 
 transcript 
 } 
 " 
 ) 
 return 
 response 
 

  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_sync_chirp2_with_timestamps 
 ( 
 audio_file 
 : 
 str 
 ) 
 - 
> cloud_speech 
 . 
 RecognizeResponse 
 : 
  
 """Transcribes an audio file using the Chirp 2 model of Google Cloud Speech-to-Text V2 API, providing word-level timestamps for each transcribed word. 
 Args: 
 audio_file (str): Path to the local audio file to be transcribed. 
 Example: "resources/audio.wav" 
 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-central1-speech.googleapis.com" 
 , 
 ) 
 ) 
 # Reads a file as bytes 
 with 
 open 
 ( 
 audio_file 
 , 
 "rb" 
 ) 
 as 
 f 
 : 
 audio_content 
 = 
 f 
 . 
 read 
 () 
 config 
 = 
 cloud_speech 
 . 
 RecognitionConfig 
 ( 
 auto_decoding_config 
 = 
 cloud_speech 
 . 
 AutoDetectDecodingConfig 
 (), 
 language_codes 
 = 
 [ 
 "en-US" 
 ], 
 model 
 = 
 "chirp_2" 
 , 
 denoiser_config 
 = 
 { 
 denoise_audio 
 : 
 True 
 , 
 # Medium snr threshold 
 snr_threshold 
 : 
 20.0 
 , 
 } 
 ) 
 request 
 = 
 cloud_speech 
 . 
 RecognizeRequest 
 ( 
 recognizer 
 = 
 f 
 "projects/ 
 { 
 PROJECT_ID 
 } 
 /locations/us-central1/recognizers/_" 
 , 
 config 
 = 
 config 
 , 
 content 
 = 
 audio_content 
 , 
 ) 
 # Transcribes the audio into text 
 response 
 = 
 client 
 . 
 recognize 
 ( 
 request 
 = 
 request 
 ) 
 for 
 result 
 in 
 response 
 . 
 results 
 : 
 print 
 ( 
 f 
 "Transcript: 
 { 
 result 
 . 
 alternatives 
 [ 
 0 
 ] 
 . 
 transcript 
 } 
 " 
 ) 
 return 
 response