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    Enable the profanity filter

    This page describes how to use Cloud Speech-to-Text to automatically detect profane words in your audio data and censor them in the transcript.

    You can enable the profanity filter by setting profanityFilter=true in the RecognitionConfig . If enabled, Cloud Speech-to-Text will attempt to detect profane words and return only the first letter followed by asterisks in the transcript (for example, f***). If this field is set to false or not set, Cloud Speech-to-Text will not attempt to filter profanities.

    The following sample demonstrates how to enable the profanity filter to recognize audio stored in a Cloud Storage bucket.

    Java

    To learn how to install and use the client library for Cloud STT, see Cloud STT client libraries . For more information, see the Cloud STT Java API reference documentation .

    To authenticate to Cloud STT, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

      import 
  
 com.google.cloud.speech.v1. RecognitionAudio 
 
 ; 
 import 
  
 com.google.cloud.speech.v1. RecognitionConfig 
 
 ; 
 import 
  
 com.google.cloud.speech.v1. RecognitionConfig 
. AudioEncoding 
 
 ; 
 import 
  
 com.google.cloud.speech.v1. RecognizeResponse 
 
 ; 
 import 
  
 com.google.cloud.speech.v1. SpeechClient 
 
 ; 
 import 
  
 com.google.cloud.speech.v1. SpeechRecognitionAlternative 
 
 ; 
 import 
  
 com.google.cloud.speech.v1. SpeechRecognitionResult 
 
 ; 
 import 
  
 java.util.List 
 ; 
 public 
  
 class 
 SpeechProfanityFilter 
  
 { 
  
 public 
  
 void 
  
 speechProfanityFilter 
 () 
  
 throws 
  
 Exception 
  
 { 
  
 String 
  
 uriPath 
  
 = 
  
 "gs://cloud-samples-tests/speech/brooklyn.flac" 
 ; 
  
 speechProfanityFilter 
 ( 
 uriPath 
 ); 
  
 } 
  
 /** 
 * Transcribe a remote audio file with multi-channel recognition 
 * 
 * @param gcsUri the path to the audio file 
 */ 
  
 public 
  
 static 
  
 void 
  
 speechProfanityFilter 
 ( 
 String 
  
 gcsUri 
 ) 
  
 throws 
  
 Exception 
  
 { 
  
 // Instantiates a client with GOOGLE_APPLICATION_CREDENTIALS 
  
 try 
  
 ( 
  SpeechClient 
 
  
 speech 
  
 = 
  
  SpeechClient 
 
 . 
 create 
 ()) 
  
 { 
  
 // Configure remote file request 
  
  RecognitionConfig 
 
  
 config 
  
 = 
  
  RecognitionConfig 
 
 . 
 newBuilder 
 () 
  
 . 
  setEncoding 
 
 ( 
  AudioEncoding 
 
 . 
 FLAC 
 ) 
  
 . 
 setLanguageCode 
 ( 
 "en-US" 
 ) 
  
 . 
  setSampleRateHertz 
 
 ( 
 16000 
 ) 
  
 . 
  setProfanityFilter 
 
 ( 
 true 
 ) 
  
 . 
 build 
 (); 
  
 // Set the remote path for the audio file 
  
  RecognitionAudio 
 
  
 audio 
  
 = 
  
  RecognitionAudio 
 
 . 
 newBuilder 
 (). 
 setUri 
 ( 
 gcsUri 
 ). 
 build 
 (); 
  
 // Use blocking call to get audio transcript 
  
  RecognizeResponse 
 
  
 response 
  
 = 
  
 speech 
 . 
 recognize 
 ( 
 config 
 , 
  
 audio 
 ); 
  
 List<SpeechRecognitionResult> 
  
 results 
  
 = 
  
 response 
 . 
  getResultsList 
 
 (); 
  
 for 
  
 ( 
  SpeechRecognitionResult 
 
  
 result 
  
 : 
  
 results 
 ) 
  
 { 
  
 // There can be several alternative transcripts for a given chunk of speech. Just use the 
  
 // first (most likely) one here. 
  
  SpeechRecognitionAlternative 
 
  
 alternative 
  
 = 
  
 result 
 . 
 getAlternativesList 
 (). 
 get 
 ( 
 0 
 ); 
  
 System 
 . 
 out 
 . 
 printf 
 ( 
 "Transcription: %s\n" 
 , 
  
 alternative 
 . 
  getTranscript 
 
 ()); 
  
 } 
  
 } 
  
 } 
 }

    Node.js

    To learn how to install and use the client library for Cloud STT, see Cloud STT client libraries . For more information, see the Cloud STT Node.js API reference documentation .

    To authenticate to Cloud STT, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

      // Filters profanity 
 /** 
 * TODO(developer): Uncomment these variables before running the sample. 
 */ 
 // const gcsUri = 'gs://my-bucket/audio.raw'; 
 async 
  
 function 
  
 syncRecognizeWithProfanityFilter 
 () 
  
 { 
  
 // Imports the Google Cloud client library 
  
 const 
  
 speech 
  
 = 
  
 require 
 ( 
 ' @google-cloud/speech 
' 
 ); 
  
 // Creates a client 
  
 const 
  
 client 
  
 = 
  
 new 
  
 speech 
 . 
  SpeechClient 
 
 (); 
  
 const 
  
 audio 
  
 = 
  
 { 
  
 uri 
 : 
  
 gcsUri 
 , 
  
 }; 
  
 const 
  
 config 
  
 = 
  
 { 
  
 encoding 
 : 
  
 'FLAC' 
 , 
  
 sampleRateHertz 
 : 
  
 16000 
 , 
  
 languageCode 
 : 
  
 'en-US' 
 , 
  
 profanityFilter 
 : 
  
 true 
 , 
  
 // set this to true 
  
 }; 
  
 const 
  
 request 
  
 = 
  
 { 
  
 audio 
 : 
  
 audio 
 , 
  
 config 
 : 
  
 config 
 , 
  
 }; 
  
 // Detects speech in the audio file 
  
 const 
  
 [ 
 response 
 ] 
  
 = 
  
 await 
  
 client 
 . 
 recognize 
 ( 
 request 
 ); 
  
 const 
  
 transcription 
  
 = 
  
 response 
 . 
 results 
  
 . 
 map 
 ( 
 result 
  
 = 
>  
 result 
 . 
 alternatives 
 [ 
 0 
 ]. 
 transcript 
 ) 
  
 . 
 join 
 ( 
 '\n' 
 ); 
  
 console 
 . 
 log 
 ( 
 `Transcription: 
 ${ 
 transcription 
 } 
 ` 
 ); 
 } 
 syncRecognizeWithProfanityFilter 
 (). 
 catch 
 ( 
 console 
 . 
 error 
 );

    Python

    To learn how to install and use the client library for Cloud STT, see Cloud STT client libraries . For more information, see the Cloud STT Python API reference documentation .

    To authenticate to Cloud STT, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

      from 
  
 google.cloud 
  
 import 
 speech 
 from 
  
 google.cloud.speech 
  
 import 
 RecognizeResponse 
 def 
  
 sync_recognize_with_profanity_filter_gcs 
 ( 
 audio_uri 
 : 
 str 
 ) 
 - 
> RecognizeResponse 
 : 
  
 """Recognizes speech from an audio file in Cloud Storage and filters out profane language. 
 Args: 
 audio_uri (str): The Cloud Storage URI of the input audio, e.g., gs://[BUCKET]/[FILE] 
 Returns: 
 cloud_speech.RecognizeResponse: The full response object which includes the transcription results. 
 """ 
 # Define the audio source 
 audio 
 = 
 { 
 "uri" 
 : 
 audio_uri 
 } 
 client 
 = 
 speech 
 . 
 SpeechClient 
 () 
 config 
 = 
 speech 
 . 
  RecognitionConfig 
 
 ( 
 encoding 
 = 
 speech 
 . 
 RecognitionConfig 
 . 
 AudioEncoding 
 . 
 FLAC 
 , 
 # Audio format 
 sample_rate_hertz 
 = 
 16000 
 , 
 language_code 
 = 
 "en-US" 
 , 
 # Enable profanity filter 
 profanity_filter 
 = 
 True 
 , 
 ) 
 response 
 = 
 client 
 . 
  recognize 
 
 ( 
 config 
 = 
 config 
 , 
 audio 
 = 
 audio 
 ) 
 for 
 result 
 in 
 response 
 . 
 results 
 : 
 alternative 
 = 
 result 
 . 
 alternatives 
 [ 
 0 
 ] 
 print 
 ( 
 f 
 "Transcript: 
 { 
 alternative 
 . 
 transcript 
 } 
 " 
 ) 
 return 
 response 
 . 
 results
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