Enable language recognition in Speech-to-Text

This page describes how to enable language recognition for audio transcription requests sent to Speech-to-Text.

In some situations, you don't know for certain what language your audio recordings contain. For example, if you publish your service, app, or product in a country with multiple official languages, you can potentially receive audio input from users in a variety of languages. This can make specifying a single language code for transcription requests significantly more difficult.

Multiple language recognition

Speech-to-Text offers a way for you to specify a set of alternative languages that your audio data might contain. When you send an audio transcription request to Speech-to-Text, you can provide a list of additional languages that the audio data might include. If you include a list of languages in your request, Speech-to-Text attempts to transcribe the audio based upon the language that best fits the sample from the alternates you provide. Speech-to-Text then labels the transcription results with the predicted language code.

This feature is ideal for apps that need to transcribe short statements like voice commands or search. You can list up to three alternative languages from among those that Speech-to-Text supports in addition to your primary language (for four languages total).

Even though you can specify alternative languages for your speech transcription request, you must still provide a primary language code in the languageCode field. Also, you should constrain the number of languages you request to a bare minimum. The fewer alternative language codes that you request helps Speech-to-Text more successfully select the correct one. Specifying just a single language produces the best results.

Enable language recognition in audio transcription requests

To specify alternative languages in your audio transcription, you must set the alternativeLanguageCodes field to a list of language codes in the RecognitionConfig parameters for the request. Speech-to-Text supports alternative language codes for all speech recognition methods: speech:recognize , speech:longrunningrecognize , and Streaming .

Use a local file

Protocol

Refer to the speech:recognize API endpoint for complete details.

To perform synchronous speech recognition, make a POST request and provide the appropriate request body. The following shows an example of a POST request using curl . The example uses the Google Cloud CLI to generate an access token. For instructions on installing the gcloud CLI, see the quickstart .

The following example shows how to request transcription of an audio file that may include speech in English, French, or German.

curl  
-s  
-H  
 "Content-Type: application/json" 
  
 \ 
  
-H  
 "Authorization: Bearer 
 $( 
gcloud  
auth  
application-default  
print-access-token ) 
 " 
  
 \ 
  
https://speech.googleapis.com/v1p1beta1/speech:recognize  
 \ 
  
--data  
 '{ 
 "config": { 
 "encoding": "LINEAR16", 
 "languageCode": "en-US", 
  "alternativeLanguageCodes": ["fr-FR", "de-DE"], 
 "model": "command_and_search" 
 }, 
 "audio": { 
 "uri": "gs://cloud-samples-tests/speech/commercial_mono.wav" 
 } 
 }' 
 > 
multi-language.txt

If the request is successful, the server returns a 200 OK HTTP status code and the response in JSON format, saved to a file named multi-language.txt .

{
  "results": [
    {
      "alternatives": [
        {
          "transcript": "hi I'd like to buy a Chromecast I'm ..."
          "confidence": 0.9466864
        }
      ],
      "languageCode": "en-us"
    },
    {
      "alternatives": [
        {
          "transcript": " let's go with the black one",
          "confidence": 0.9829583
        }
      ],
      "languageCode": "en-us"
    },
  ]
}

Java

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

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

  /** 
 * Transcribe a local audio file with multi-language recognition 
 * 
 * @param fileName the path to the audio file 
 */ 
 public 
  
 static 
  
 void 
  
 transcribeMultiLanguage 
 ( 
 String 
  
 fileName 
 ) 
  
 throws 
  
 Exception 
  
 { 
  
 Path 
  
 path 
  
 = 
  
 Paths 
 . 
 get 
 ( 
 fileName 
 ); 
  
 // Get the contents of the local audio file 
  
 byte 
 [] 
  
 content 
  
 = 
  
 Files 
 . 
 readAllBytes 
 ( 
 path 
 ); 
  
 try 
  
 ( 
 SpeechClient 
  
 speechClient 
  
 = 
  
 SpeechClient 
 . 
 create 
 ()) 
  
 { 
  
 RecognitionAudio 
  
 recognitionAudio 
  
 = 
  
 RecognitionAudio 
 . 
 newBuilder 
 (). 
 setContent 
 ( 
 ByteString 
 . 
 copyFrom 
 ( 
 content 
 )). 
 build 
 (); 
  
 ArrayList<String> 
  
 languageList 
  
 = 
  
 new 
  
 ArrayList 
<> (); 
  
 languageList 
 . 
 add 
 ( 
 "es-ES" 
 ); 
  
 languageList 
 . 
 add 
 ( 
 "en-US" 
 ); 
  
 // Configure request to enable multiple languages 
  
 RecognitionConfig 
  
 config 
  
 = 
  
 RecognitionConfig 
 . 
 newBuilder 
 () 
  
 . 
 setEncoding 
 ( 
 AudioEncoding 
 . 
 LINEAR16 
 ) 
  
 . 
 setSampleRateHertz 
 ( 
 16000 
 ) 
  
 . 
 setLanguageCode 
 ( 
 "ja-JP" 
 ) 
  
 . 
 addAllAlternativeLanguageCodes 
 ( 
 languageList 
 ) 
  
 . 
 build 
 (); 
  
 // Perform the transcription request 
  
 RecognizeResponse 
  
 recognizeResponse 
  
 = 
  
 speechClient 
 . 
 recognize 
 ( 
 config 
 , 
  
 recognitionAudio 
 ); 
  
 // Print out the results 
  
 for 
  
 ( 
 SpeechRecognitionResult 
  
 result 
  
 : 
  
 recognizeResponse 
 . 
 getResultsList 
 ()) 
  
 { 
  
 // There can be several alternative transcripts for a given chunk of speech. Just use the 
  
 // first (most likely) one here. 
  
 SpeechRecognitionAlternative 
  
 alternative 
  
 = 
  
 result 
 . 
 getAlternatives 
 ( 
 0 
 ); 
  
 System 
 . 
 out 
 . 
 format 
 ( 
 "Transcript : %s\n\n" 
 , 
  
 alternative 
 . 
 getTranscript 
 ()); 
  
 } 
  
 } 
 }

Node.js

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

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

  const 
  
 fs 
  
 = 
  
 require 
 ( 
 'fs' 
 ); 
 // Imports the Google Cloud client library 
 const 
  
 speech 
  
 = 
  
 require 
 ( 
 ' @google-cloud/speech 
' 
 ). 
 v1p1beta1 
 ; 
 // Creates a client 
 const 
  
 client 
  
 = 
  
 new 
  
 speech 
 . 
  SpeechClient 
 
 (); 
 /** 
 * TODO(developer): Uncomment the following lines before running the sample. 
 */ 
 // const fileName = 'Local path to audio file, e.g. /path/to/audio.raw'; 
 const 
  
 config 
  
 = 
  
 { 
  
 encoding 
 : 
  
 'LINEAR16' 
 , 
  
 sampleRateHertz 
 : 
  
 44100 
 , 
  
 languageCode 
 : 
  
 'en-US' 
 , 
  
 alternativeLanguageCodes 
 : 
  
 [ 
 'es-ES' 
 , 
  
 'en-US' 
 ], 
 }; 
 const 
  
 audio 
  
 = 
  
 { 
  
 content 
 : 
  
 fs 
 . 
 readFileSync 
 ( 
 fileName 
 ). 
 toString 
 ( 
 'base64' 
 ), 
 }; 
 const 
  
 request 
  
 = 
  
 { 
  
 config 
 : 
  
 config 
 , 
  
 audio 
 : 
  
 audio 
 , 
 }; 
 const 
  
 [ 
 response 
 ] 
  
 = 
  
 await 
  
 client 
 . 
 recognize 
 ( 
 request 
 ); 
 const 
  
 transcription 
  
 = 
  
 response 
 . 
 results 
  
 . 
 map 
 ( 
 result 
  
 = 
>  
 result 
 . 
 alternatives 
 [ 
 0 
 ]. 
 transcript 
 ) 
  
 . 
 join 
 ( 
 '\n' 
 ); 
 console 
 . 
 log 
 ( 
 `Transcription: 
 ${ 
 transcription 
 } 
 ` 
 );

Python

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

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

  from 
  
 google.cloud 
  
 import 
 speech_v1p1beta1 
 as 
 speech 
 client 
 = 
 speech 
 . 
 SpeechClient 
 () 
 speech_file 
 = 
 "resources/multi.wav" 
 first_lang 
 = 
 "en-US" 
 second_lang 
 = 
 "es" 
 with 
 open 
 ( 
 speech_file 
 , 
 "rb" 
 ) 
 as 
 audio_file 
 : 
 content 
 = 
 audio_file 
 . 
 read 
 () 
 audio 
 = 
 speech 
 . 
 RecognitionAudio 
 ( 
 content 
 = 
 content 
 ) 
 config 
 = 
 speech 
 . 
 RecognitionConfig 
 ( 
 encoding 
 = 
 speech 
 . 
 RecognitionConfig 
 . 
 AudioEncoding 
 . 
 LINEAR16 
 , 
 sample_rate_hertz 
 = 
 44100 
 , 
 audio_channel_count 
 = 
 2 
 , 
 language_code 
 = 
 first_lang 
 , 
 alternative_language_codes 
 = 
 [ 
 second_lang 
 ], 
 ) 
 print 
 ( 
 "Waiting for operation to complete..." 
 ) 
 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 
 } 
 : 
 { 
 alternative 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Transcript: 
 { 
 alternative 
 . 
 transcript 
 } 
 " 
 ) 
 return 
 response 
 . 
 results

Use a remote file

Java

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

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

  /** 
 * Transcribe a remote audio file with multi-language recognition 
 * 
 * @param gcsUri the path to the remote audio file 
 */ 
 public 
  
 static 
  
 void 
  
 transcribeMultiLanguageGcs 
 ( 
 String 
  
 gcsUri 
 ) 
  
 throws 
  
 Exception 
  
 { 
  
 try 
  
 ( 
 SpeechClient 
  
 speechClient 
  
 = 
  
 SpeechClient 
 . 
 create 
 ()) 
  
 { 
  
 ArrayList<String> 
  
 languageList 
  
 = 
  
 new 
  
 ArrayList 
<> (); 
  
 languageList 
 . 
 add 
 ( 
 "es-ES" 
 ); 
  
 languageList 
 . 
 add 
 ( 
 "en-US" 
 ); 
  
 // Configure request to enable multiple languages 
  
 RecognitionConfig 
  
 config 
  
 = 
  
 RecognitionConfig 
 . 
 newBuilder 
 () 
  
 . 
 setEncoding 
 ( 
 AudioEncoding 
 . 
 LINEAR16 
 ) 
  
 . 
 setSampleRateHertz 
 ( 
 16000 
 ) 
  
 . 
 setLanguageCode 
 ( 
 "ja-JP" 
 ) 
  
 . 
 addAllAlternativeLanguageCodes 
 ( 
 languageList 
 ) 
  
 . 
 build 
 (); 
  
 // Set the remote path for the audio file 
  
 RecognitionAudio 
  
 audio 
  
 = 
  
 RecognitionAudio 
 . 
 newBuilder 
 (). 
 setUri 
 ( 
 gcsUri 
 ). 
 build 
 (); 
  
 // Use non-blocking call for getting file transcription 
  
 OperationFuture<LongRunningRecognizeResponse 
 , 
  
 LongRunningRecognizeMetadata 
>  
 response 
  
 = 
  
 speechClient 
 . 
 longRunningRecognizeAsync 
 ( 
 config 
 , 
  
 audio 
 ); 
  
 while 
  
 ( 
 ! 
 response 
 . 
 isDone 
 ()) 
  
 { 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Waiting for response..." 
 ); 
  
 Thread 
 . 
 sleep 
 ( 
 10000 
 ); 
  
 } 
  
 for 
  
 ( 
 SpeechRecognitionResult 
  
 result 
  
 : 
  
 response 
 . 
 get 
 (). 
 getResultsList 
 ()) 
  
 { 
  
 // 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 
 ); 
  
 // Print out the result 
  
 System 
 . 
 out 
 . 
 printf 
 ( 
 "Transcript : %s\n\n" 
 , 
  
 alternative 
 . 
 getTranscript 
 ()); 
  
 } 
  
 } 
 }

Node.js

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

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

  // Imports the Google Cloud client library 
 const 
  
 speech 
  
 = 
  
 require 
 ( 
 ' @google-cloud/speech 
' 
 ). 
 v1p1beta1 
 ; 
 // Creates a client 
 const 
  
 client 
  
 = 
  
 new 
  
 speech 
 . 
  SpeechClient 
 
 (); 
 /** 
 * TODO(developer): Uncomment the following line before running the sample. 
 */ 
 // const uri = path to GCS audio file e.g. `gs:/bucket/audio.wav`; 
 const 
  
 config 
  
 = 
  
 { 
  
 encoding 
 : 
  
 'LINEAR16' 
 , 
  
 sampleRateHertz 
 : 
  
 44100 
 , 
  
 languageCode 
 : 
  
 'en-US' 
 , 
  
 alternativeLanguageCodes 
 : 
  
 [ 
 'es-ES' 
 , 
  
 'en-US' 
 ], 
 }; 
 const 
  
 audio 
  
 = 
  
 { 
  
 uri 
 : 
  
 gcsUri 
 , 
 }; 
 const 
  
 request 
  
 = 
  
 { 
  
 config 
 : 
  
 config 
 , 
  
 audio 
 : 
  
 audio 
 , 
 }; 
 const 
  
 [ 
 operation 
 ] 
  
 = 
  
 await 
  
 client 
 . 
 longRunningRecognize 
 ( 
 request 
 ); 
 const 
  
 [ 
 response 
 ] 
  
 = 
  
 await 
  
 operation 
 . 
 promise 
 (); 
 const 
  
 transcription 
  
 = 
  
 response 
 . 
 results 
  
 . 
 map 
 ( 
 result 
  
 = 
>  
 result 
 . 
 alternatives 
 [ 
 0 
 ]. 
 transcript 
 ) 
  
 . 
 join 
 ( 
 '\n' 
 ); 
 console 
 . 
 log 
 ( 
 `Transcription: 
 ${ 
 transcription 
 } 
 ` 
 );

Python

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

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

  from 
  
 google.cloud 
  
 import 
 speech_v1p1beta1 
 as 
 speech 
 def 
  
 transcribe_file_with_multilanguage_gcs 
 ( 
 audio_uri 
 : 
 str 
 ) 
 - 
> str 
 : 
  
 """Transcribe a remote audio file with multi-language recognition 
 Args: 
 audio_uri (str): The Google Cloud Storage path to an audio file. 
 E.g., gs://[BUCKET]/[FILE] 
 Returns: 
 str: The generated transcript from the audio file provided. 
 """ 
 client 
 = 
 speech 
 . 
 SpeechClient 
 () 
 first_language 
 = 
 "es-ES" 
 alternate_languages 
 = 
 [ 
 "en-US" 
 , 
 "fr-FR" 
 ] 
 # Configure request to enable multiple languages 
 recognition_config 
 = 
 speech 
 . 
 RecognitionConfig 
 ( 
 encoding 
 = 
 speech 
 . 
 RecognitionConfig 
 . 
 AudioEncoding 
 . 
 FLAC 
 , 
 sample_rate_hertz 
 = 
 44100 
 , 
 language_code 
 = 
 first_language 
 , 
 alternative_language_codes 
 = 
 alternate_languages 
 , 
 ) 
 # Set the remote path for the audio file 
 audio 
 = 
 speech 
 . 
 RecognitionAudio 
 ( 
 uri 
 = 
 audio_uri 
 ) 
 # Use non-blocking call for getting file transcription 
 response 
 = 
 client 
 . 
 long_running_recognize 
 ( 
 config 
 = 
 recognition_config 
 , 
 audio 
 = 
 audio 
 ) 
 . 
 result 
 ( 
 timeout 
 = 
 300 
 ) 
 transcript_builder 
 = 
 [] 
 for 
 i 
 , 
 result 
 in 
 enumerate 
 ( 
 response 
 . 
 results 
 ): 
 alternative 
 = 
 result 
 . 
 alternatives 
 [ 
 0 
 ] 
 transcript_builder 
 . 
 append 
 ( 
 "-" 
 * 
 20 
 + 
 " 
 \n 
 " 
 ) 
 transcript_builder 
 . 
 append 
 ( 
 f 
 "First alternative of result 
 { 
 i 
 } 
 : 
 { 
 alternative 
 } 
 " 
 ) 
 transcript_builder 
 . 
 append 
 ( 
 f 
 "Transcript: 
 { 
 alternative 
 . 
 transcript 
 } 
  
 \n 
 " 
 ) 
 transcript 
 = 
 "" 
 . 
 join 
 ( 
 transcript_builder 
 ) 
 print 
 ( 
 transcript 
 ) 
 return 
 transcript

Enable language recognition in Speech-to-Text Stay organized with collections Save and categorize content based on your preferences.

Multiple language recognition

Enable language recognition in audio transcription requests

Use a local file

Protocol

Java

Node.js

Python

Use a remote file

Java

Node.js

Python

Enable language recognition in Speech-to-Text